- able(Iterator<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
-
Wraps an iterator as an iterable
- abs(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- accept(T) - Method in interface org.deeplearning4j.berkeley.Filter
-
- accumulateScore(double) - Method in interface org.deeplearning4j.nn.api.Model
-
Sets a rolling tally for the score.
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- accumulateScore(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- accuracy() - Method in class org.deeplearning4j.eval.Evaluation
-
Accuracy:
(TP + TN) / (P + N)
- AccuracyPlotterIterationListener - Class in org.deeplearning4j.plot.iterationlistener
-
Reference: https://cs231n.github.io/neural-networks-3/
- AccuracyPlotterIterationListener(int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.AccuracyPlotterIterationListener
-
- AccuracyPlotterIterationListener(int, NeuralNetPlotter) - Constructor for class org.deeplearning4j.plot.iterationlistener.AccuracyPlotterIterationListener
-
- AccuracyPlotterIterationListener(int, NeuralNetPlotter, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.AccuracyPlotterIterationListener
-
- AccuracyPlotterIterationListener(int, MultiLayerNetwork, DataSet) - Constructor for class org.deeplearning4j.plot.iterationlistener.AccuracyPlotterIterationListener
-
- AccuracyPlotterIterationListener(int, MultiLayerNetwork, DataSet, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.AccuracyPlotterIterationListener
-
- AccuracyPlotterIterationListener(int, MultiLayerNetwork, INDArray, INDArray) - Constructor for class org.deeplearning4j.plot.iterationlistener.AccuracyPlotterIterationListener
-
- AccuracyPlotterIterationListener(int) - Constructor for class org.deeplearning4j.plot.iterationlistener.AccuracyPlotterIterationListener
-
- activate(boolean) - Method in interface org.deeplearning4j.nn.api.Layer
-
Trigger an activation with the last specified input
- activate(INDArray, boolean) - Method in interface org.deeplearning4j.nn.api.Layer
-
Initialize the layer with the given input
and return the activation for this layer
given this input
- activate() - Method in interface org.deeplearning4j.nn.api.Layer
-
Trigger an activation with the last specified input
- activate(INDArray) - Method in interface org.deeplearning4j.nn.api.Layer
-
Initialize the layer with the given input
and return the activation for this layer
given this input
- activate(boolean) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- activate(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- activate(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- activate() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- activate(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- activate(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- activate() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- activate(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- activate(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- activate(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- activate(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- activate(boolean) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- activate() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- activate(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- activate(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- activate(boolean) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- activate() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- activate(boolean) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
Reconstructs the visible INPUT.
- activate(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- activate(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- activate(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- activate() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- activate(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- activate(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- activate(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- activate() - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- activate(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- activate(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- activate() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Triggers the activation of the last hidden layer ie: not logistic regression
- activate(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Triggers the activation for a given layer
- activate(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- activate(int, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Triggers the activation of the given layer
- activate(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- activate(INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- activation(String) - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- activationFromPrevLayer(int, INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Calculate activation from previous layer including pre processing where necessary
- activationFunction - Variable in class org.deeplearning4j.nn.conf.layers.Layer
-
- activationFunction - Variable in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- activationMean() - Method in interface org.deeplearning4j.nn.api.Layer
-
Calculate the mean representation
for the activation for this layer
- activationMean() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- activationMean() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- activationMean() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- activationMean() - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- activationMean() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- ActivationMeanIterationListener - Class in org.deeplearning4j.plot.iterationlistener
-
- ActivationMeanIterationListener(int) - Constructor for class org.deeplearning4j.plot.iterationlistener.ActivationMeanIterationListener
-
- AdaDeltaUpdater - Class in org.deeplearning4j.nn.updater
-
- AdaDeltaUpdater() - Constructor for class org.deeplearning4j.nn.updater.AdaDeltaUpdater
-
- adaGrad - Variable in class org.deeplearning4j.plot.Tsne
-
- AdaGradUpdater - Class in org.deeplearning4j.nn.updater
-
Ada grad updater
- AdaGradUpdater() - Constructor for class org.deeplearning4j.nn.updater.AdaGradUpdater
-
- AdamUpdater - Class in org.deeplearning4j.nn.updater
-
- AdamUpdater() - Constructor for class org.deeplearning4j.nn.updater.AdamUpdater
-
- add(E, double) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- add(T, T) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Increments the entry specified by actual and predicted by one.
- add(T, T, int) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Increments the entry specified by actual and predicted by count.
- add(ConfusionMatrix<T>) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Adds the entries from another confusion matrix to this one.
- add(E) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- add(Object, int) - Method in class org.deeplearning4j.util.Index
-
- add(Object) - Method in class org.deeplearning4j.util.Index
-
- add(Pair<K, V>) - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Adds the specified element to this applyTransformToDestination if it is not already present
(optional operation).
- add(K, V) - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
- addAll(Collection<? extends E>) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- addAll(Collection<? extends Pair<K, V>>) - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Adds all of the elements in the specified collection to this applyTransformToDestination if
they're not already present (optional operation).
- addClusterInfo(String) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- addColumn(List<String>) - Method in class org.deeplearning4j.util.StringGrid
-
- addExp(float[], int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- addExp_Old(float[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Similar to logAdd, but without the final log.
- addNewClusterWithCenter(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- addNewClusterWithCenter(INDArray) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- addPoint(INDArray) - Method in class org.deeplearning4j.clustering.Cluster
-
- addPoint(INDArray, boolean) - Method in class org.deeplearning4j.clustering.Cluster
-
- addPoint(Point) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- addPoint(Point, boolean) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- addPoint(INDArray) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- addPoint(INDArray, boolean) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- addPoints(List<INDArray>) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- addPoints(List<INDArray>, boolean) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- addRow(List<String>) - Method in class org.deeplearning4j.util.StringGrid
-
- addToConfusion(Integer, Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
Adds to the confusion matrix
- addVariable(String) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- adjustedrSquared(double, int, int) - Static method in class org.deeplearning4j.util.MathUtils
-
This calculates the adjusted r^2 including degrees of freedom.
- ALF - Variable in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- allMatches(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- allowEmptyClusters - Variable in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- ancestor(int, Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Returns the ancestor of the given tree
- appendTo(String, File) - Static method in class org.deeplearning4j.util.FileOperations
-
- appendToEach(String, int) - Method in class org.deeplearning4j.util.StringGrid
-
- applyClusteringStrategy() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- applyDropConnect(Layer, String) - Static method in class org.deeplearning4j.util.Dropout
-
Apply drop connect to the given variable
- applyDropout(INDArray, double, INDArray) - Static method in class org.deeplearning4j.util.Dropout
-
Apply dropout to the given input
and return the drop out mask used
- applyDropOutIfNecessary(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- applyOptimization(OptimisationStrategy, ClusterSet, ClusterSetInfo, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- applyTo(List<Point>) - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- applyTo(List<Point>) - Method in interface org.deeplearning4j.clustering.algorithm.ClusteringAlgorithm
-
- applyTo(List<INDArray>) - Method in interface org.deeplearning4j.clustering.ClusteringAlgorithm
-
- approxEquals(Counter<E>, double) - Method in class org.deeplearning4j.berkeley.Counter
-
- approxExp(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- approxLog(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- approxPow(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- ArchiveUtils - Class in org.deeplearning4j.util
-
- ArchiveUtils() - Constructor for class org.deeplearning4j.util.ArchiveUtils
-
- argMax() - Method in class org.deeplearning4j.berkeley.Counter
-
Finds the key with maximum count.
- argMax() - Method in class org.deeplearning4j.berkeley.CounterMap
-
Finds the key with maximum count.
- argsToMap(String[]) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Parses command line arguments into a Map.
- argsToMap(String[], Map<String, Integer>) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Parses command line arguments into a Map.
- argsToProperties(String[]) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- argsToProperties(String[], Map) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- arrayToString(String[]) - Static method in class org.deeplearning4j.util.StringUtils
-
Given an array of strings, return a comma-separated list of its elements.
- asciify(String) - Method in class org.deeplearning4j.util.FingerPrintKeyer
-
- asCounter() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
Returns a counter whose keys are the elements in this priority queue, and
whose counts are the priorities in this queue.
- asImageMiniBatches(File, int, int) - Method in class org.deeplearning4j.util.ImageLoader
-
Slices up an image in to a mini batch.
- asMatrix(File) - Method in class org.deeplearning4j.util.ImageLoader
-
- asMinPriorityQueue() - Method in class org.deeplearning4j.berkeley.Counter
-
Warning: all priorities are the negative of their counts in the counter
here
- asPriorityQueue() - Method in class org.deeplearning4j.berkeley.Counter
-
Builds a priority queue whose elements are the counter's elements, and
whose priorities are those elements' counts in the counter.
- asRowVector(File) - Method in class org.deeplearning4j.util.ImageLoader
-
- AutoEncoder - Class in org.deeplearning4j.nn.conf.layers
-
Autoencoder.
- AutoEncoder - Class in org.deeplearning4j.nn.layers.feedforward.autoencoder
-
Autoencoder.
- AutoEncoder(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- AutoEncoder(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- AutoEncoder.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- backprop(INDArray, Layer) - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor
-
Reverse the preProcess during backprop.
- backprop - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- backprop - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- backprop(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
Whether to do back prop or not
- backprop(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- backprop(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
-
- backprop(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- backprop(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- backprop(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- backprop(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- backprop(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
-
- backprop(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- backprop(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.UnitVarianceProcessor
-
- backprop(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanAndUnitVariancePreProcessor
-
- backprop(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanPrePreProcessor
-
- backprop() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- backpropGradient(INDArray) - Method in interface org.deeplearning4j.nn.api.Layer
-
Calculate the gradient relative to the error in the next layer
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- backpropGradient(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- backPropGradient2() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Do a back prop iteration.
- backPropGradientR(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Do a back prop iteration.
- BackTrackLineSearch - Class in org.deeplearning4j.optimize.solvers
-
- BackTrackLineSearch(Model, StepFunction, ConvexOptimizer) - Constructor for class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- BackTrackLineSearch(Model, ConvexOptimizer) - Constructor for class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- BarnesHutTsne - Class in org.deeplearning4j.plot
-
Barnes hut algorithm for TSNE, uses a dual tree approximation approach.
- BarnesHutTsne(INDArray, INDArray, int, double, double, int, int, int, double, double, double) - Constructor for class org.deeplearning4j.plot.BarnesHutTsne
-
- BarnesHutTsne(INDArray, INDArray, int, String, double, boolean, int, double, double, double, double, int, boolean, boolean, int, double, double, boolean, double, double) - Constructor for class org.deeplearning4j.plot.BarnesHutTsne
-
- BarnesHutTsne.Builder - Class in org.deeplearning4j.plot
-
- BaseClusteringAlgorithm - Class in org.deeplearning4j.clustering.algorithm
-
adapted to ndarray matrices
- BaseClusteringAlgorithm(ClusteringStrategy) - Constructor for class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- BaseClusteringStrategy - Class in org.deeplearning4j.clustering.algorithm.strategy
-
- BaseClusteringStrategy(ClusteringStrategyType, Integer, String, boolean) - Constructor for class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- BaseDataFetcher - Class in org.deeplearning4j.datasets.fetchers
-
A base class for assisting with creation of matrices
with the data applyTransformToDestination fetcher
- BaseDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- BaseDatasetIterator - Class in org.deeplearning4j.datasets.iterator
-
Baseline implementation includes
control over the data fetcher and some basic
getters for metadata
- BaseDatasetIterator(int, int, DataSetFetcher) - Constructor for class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- BaseInputPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
- BaseInputPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.BaseInputPreProcessor
-
- BaseLayer<LayerConfT extends Layer> - Class in org.deeplearning4j.nn.layers
-
A layer with a bias
and activation function
- BaseLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.BaseLayer
-
- BaseLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.BaseLayer
-
- BaseOptimizer - Class in org.deeplearning4j.optimize.solvers
-
Base optimizer
- BaseOptimizer(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- BaseOptimizer(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- BaseOutputLayer - Class in org.deeplearning4j.nn.conf.layers
-
- BaseOutputLayer(BaseOutputLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.BaseOutputLayer
-
- BaseOutputLayer<LayerConfT extends BaseOutputLayer> - Class in org.deeplearning4j.nn.layers
-
Output layer with different objective
incooccurrences for different objectives.
- BaseOutputLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- BaseOutputLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- BaseOutputLayer.Builder<T extends BaseOutputLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- BasePretrainNetwork - Class in org.deeplearning4j.nn.conf.layers
-
- BasePretrainNetwork(BasePretrainNetwork.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
-
- BasePretrainNetwork<LayerConfT extends BasePretrainNetwork> - Class in org.deeplearning4j.nn.layers
-
Baseline class for any Neural Network used
as a layer in a deep network *
- BasePretrainNetwork(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- BasePretrainNetwork(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- BasePretrainNetwork.Builder<T extends BasePretrainNetwork.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- BaseRecurrentLayer - Class in org.deeplearning4j.nn.conf.layers
-
- BaseRecurrentLayer(BaseRecurrentLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer
-
- BaseRecurrentLayer<LayerConfT extends Layer> - Class in org.deeplearning4j.nn.layers.recurrent
-
- BaseRecurrentLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
- BaseRecurrentLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
- BaseRecurrentLayer.Builder<T extends BaseRecurrentLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- BaseUpdater - Class in org.deeplearning4j.nn.updater
-
- BaseUpdater() - Constructor for class org.deeplearning4j.nn.updater.BaseUpdater
-
- batch() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- batch - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Batch size
- batch() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Batch size
- batch() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- batchSize() - Method in interface org.deeplearning4j.nn.api.Model
-
The current inputs batch size
- batchSize - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- batchSize(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- batchSize() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- batchSize() - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- batchSize() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- batchSize() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
The batch size for the optimizer
- batchSize() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- batchSize() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- bernoullis(double, double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
This will return the bernoulli trial for the given event.
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.GRUParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.ImageLSTMParamInitializer
-
- binarize(int) - Method in class org.deeplearning4j.datasets.vectorizer.ImageVectorizer
-
Binarize the data based on the threshold (anything < threshold is zero)
This is used for making the image brightness agnostic.
- binarize() - Method in class org.deeplearning4j.datasets.vectorizer.ImageVectorizer
-
Binarize the data based on the threshold (anything < threshold is zero)
This is used for making the image brightness agnostic.
- binomial(RandomGenerator, int, double) - Static method in class org.deeplearning4j.util.MathUtils
-
Generates a binomial distributed number using
the given rng
- BinomialDistribution - Class in org.deeplearning4j.nn.conf.distribution
-
A binomial distribution.
- BinomialDistribution(int, double) - Constructor for class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
Create a distribution
- BinomialSamplingPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
Binomial sampling pre processor
- BinomialSamplingPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.DenseLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.GravesLSTM.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.GRU.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.ImageLSTM.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.OutputLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.RBM.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.RecursiveAutoEncoder.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.RnnOutputLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Return a configuration based on this builder
- build() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
Build the multi layer network
based on this neural network and
overr ridden parameters
- build() - Method in class org.deeplearning4j.optimize.Solver.Builder
-
- build() - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- build() - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- buildCounter(MapFactory<V, Double>) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.AutoEncoder.Builder
-
- Builder(double) - Constructor for class org.deeplearning4j.nn.conf.layers.AutoEncoder.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- Builder(LossFunctions.LossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer.Builder
-
- Builder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- Builder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- Builder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.DenseLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.GravesLSTM.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.GRU.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.ImageLSTM.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- Builder(LossFunctions.LossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.OutputLayer.Builder
-
- Builder(RBM.HiddenUnit, RBM.VisibleUnit) - Constructor for class org.deeplearning4j.nn.conf.layers.RBM.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.RBM.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.RecursiveAutoEncoder.Builder
-
- Builder(LossFunctions.LossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.RnnOutputLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType, int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType, int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- Builder() - Constructor for class org.deeplearning4j.optimize.Solver.Builder
-
- Builder() - Constructor for class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- Builder() - Constructor for class org.deeplearning4j.plot.Tsne.Builder
-
- buildFromData(List<DataPoint>) - Static method in class org.deeplearning4j.clustering.vptree.VPTree
-
- buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory
-
- buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.HashMapFactory
-
- buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.IdentityHashMapFactory
-
- buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.TreeMapFactory
-
- buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.WeakHashMapFactory
-
- byteDesc(long) - Static method in class org.deeplearning4j.util.StringUtils
-
Return an abbreviated English-language desc of the byte length
- byteToHexString(byte[], int, int) - Static method in class org.deeplearning4j.util.StringUtils
-
Given an array of bytes it will convert the bytes to a hex string
representation of the bytes
- byteToHexString(byte[]) - Static method in class org.deeplearning4j.util.StringUtils
-
Same as byteToHexString(bytes, 0, bytes.length).
- ByteUtil - Class in org.deeplearning4j.util
-
- ByteUtil() - Constructor for class org.deeplearning4j.util.ByteUtil
-
- calcGradient(Gradient, INDArray) - Method in interface org.deeplearning4j.nn.api.Layer
-
Calculate the gradient
- calcGradient(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- calcGradient(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- calcGradient(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- calcGradient(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- calcGradient(Gradient, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- calcGradient(Gradient, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- calcL1() - Method in interface org.deeplearning4j.nn.api.Layer
-
Calculate the l1 regularization term
0.0 if regularization is not used.
- calcL1() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- calcL1() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- calcL1() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- calcL1() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- calcL1() - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- calcL1() - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- calcL1() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- calcL2() - Method in interface org.deeplearning4j.nn.api.Layer
-
Calculate the l2 regularization term
0.0 if regularization is not used.
- calcL2() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- calcL2() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- calcL2() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- calcL2() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- calcL2() - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- calcL2() - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- calcL2() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- calculate(INDArray, int, double) - Method in class org.deeplearning4j.plot.Tsne
-
- calculateDelta(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- call(I) - Method in interface org.deeplearning4j.berkeley.MyMethod
-
- capitalize(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Uppercases the first character of a string.
- Cell - Class in org.deeplearning4j.clustering.quadtree
-
A cell representing a bounding box forthe quad tree
- Cell(double, double, double, double) - Constructor for class org.deeplearning4j.clustering.quadtree.Cell
-
- Cell - Class in org.deeplearning4j.clustering.sptree
-
- Cell(int) - Constructor for class org.deeplearning4j.clustering.sptree.Cell
-
- cgBackTrack(List<INDArray>, INDArray) - Method in class org.deeplearning4j.optimize.solvers.StochasticHessianFree
-
Iterate through the current list of gradients
and backtrack upon an optimal step
that improves the current score
- checkGradients(MultiLayerNetwork, double, double, boolean, boolean, INDArray, INDArray, boolean) - Static method in class org.deeplearning4j.gradientcheck.GradientCheckUtil
-
Check backprop gradients for a MultiLayerNetwork.
- children() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- chiSquare2by2(int, int, int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Find a 2x2 chi-square value.
- choleskyFromMatrix(RealMatrix) - Method in class org.deeplearning4j.util.MathUtils
-
This will return the cholesky decomposition of
the given matrix
- clamp(int, int, int) - Static method in class org.deeplearning4j.util.MathUtils
-
Clamps the value to a discrete value
- CLASS - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
-
- classCount(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the number of times the given label
has actually occurred
- Classifier - Interface in org.deeplearning4j.nn.api
-
A classifier (this is for supervised learning)
- classifier() - Method in interface org.deeplearning4j.nn.api.SequenceClassifier
-
- ClassifierOverride - Class in org.deeplearning4j.nn.conf.override
-
Deprecated.
- ClassifierOverride(int) - Constructor for class org.deeplearning4j.nn.conf.override.ClassifierOverride
-
Deprecated.
- ClassifierOverride() - Constructor for class org.deeplearning4j.nn.conf.override.ClassifierOverride
-
Deprecated.
- classify(INDArray) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- classify(INDArray, Class<? extends Accumulation>) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- classifyPoint(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- classifyPoint(Point, boolean) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- classifyPoint(ClusterSet, Point) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- classifyPoints() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- classifyPoints(List<Point>) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- classifyPoints(List<Point>, boolean) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- classifyPoints(ClusterSet, List<Point>, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- clear() - Method in class org.deeplearning4j.berkeley.Counter
-
- clear() - Method in interface org.deeplearning4j.nn.api.Model
-
Clear input
- clear() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- clear() - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
Clear residual parameters (useful for returning a gradient and then clearing old objects)
- clear() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- clear() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- clear() - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- clear() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Clear the inputs.
- clear() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- clear() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- clear() - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
Removes all of the mappings from this map (optional operation).
- clear() - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Removes all of the elements from this applyTransformToDestination (optional operation).
- clearVariables() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- clone() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
Returns a clone of this priority queue.
- clone() - Method in interface org.deeplearning4j.nn.api.Layer
-
Clone the layer
- clone() - Method in class org.deeplearning4j.nn.conf.distribution.Distribution
-
- clone() - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- clone() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- clone() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Creates and returns a deep copy of the configuration.
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.BaseInputPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.UnitVarianceProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.stepfunctions.StepFunction
-
- clone() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- clone() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- close() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
-
- close() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
Close any resources opened by the manager.
- close() - Method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- Cluster - Class in org.deeplearning4j.clustering
-
- Cluster() - Constructor for class org.deeplearning4j.clustering.Cluster
-
- Cluster(String) - Constructor for class org.deeplearning4j.clustering.Cluster
-
- Cluster(INDArray) - Constructor for class org.deeplearning4j.clustering.Cluster
-
- Cluster(String, INDArray) - Constructor for class org.deeplearning4j.clustering.Cluster
-
- Cluster(INDArray, List<INDArray>) - Constructor for class org.deeplearning4j.clustering.Cluster
-
- Cluster - Class in org.deeplearning4j.clustering.cluster
-
- Cluster() - Constructor for class org.deeplearning4j.clustering.cluster.Cluster
-
- Cluster(Point, String) - Constructor for class org.deeplearning4j.clustering.cluster.Cluster
-
- clusterColumn(int) - Method in class org.deeplearning4j.util.StringGrid
-
- ClusterInfo - Class in org.deeplearning4j.clustering.cluster.info
-
- ClusterInfo() - Constructor for class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- ClusterInfo(boolean) - Constructor for class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- ClusteringAlgorithm - Interface in org.deeplearning4j.clustering.algorithm
-
- ClusteringAlgorithm - Interface in org.deeplearning4j.clustering
-
- ClusteringAlgorithmCondition - Interface in org.deeplearning4j.clustering.algorithm.condition
-
- ClusteringOptimization - Class in org.deeplearning4j.clustering.algorithm.optimisation
-
- ClusteringOptimization(ClusteringOptimizationType, double) - Constructor for class org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimization
-
- ClusteringOptimizationType - Enum in org.deeplearning4j.clustering.algorithm.optimisation
-
- ClusteringStrategy - Interface in org.deeplearning4j.clustering.algorithm.strategy
-
- ClusteringStrategyType - Enum in org.deeplearning4j.clustering.algorithm.strategy
-
- ClusterSet - Class in org.deeplearning4j.clustering.cluster
-
- ClusterSet() - Constructor for class org.deeplearning4j.clustering.cluster.ClusterSet
-
- ClusterSet(String) - Constructor for class org.deeplearning4j.clustering.cluster.ClusterSet
-
- ClusterSet - Class in org.deeplearning4j.clustering
-
- ClusterSet() - Constructor for class org.deeplearning4j.clustering.ClusterSet
-
- ClusterSet(INDArray) - Constructor for class org.deeplearning4j.clustering.ClusterSet
-
- ClusterSet(Class<? extends Accumulation>) - Constructor for class org.deeplearning4j.clustering.ClusterSet
-
- ClusterSetInfo - Class in org.deeplearning4j.clustering.cluster.info
-
- ClusterSetInfo() - Constructor for class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- ClusterSetInfo(boolean) - Constructor for class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- ClusterUtils - Class in org.deeplearning4j.clustering.cluster
-
Basic cluster utilities
- ClusterUtils() - Constructor for class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- CnnToFeedForwardPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow CNN and standard feed-forward network layers to be used together.
For example, CNN -> Denselayer
This does two things:
(b) Reshapes 4d activations out of CNN layer, with shape
[numExamples, numChannels, inputHeight, inputWidth]) into 2d activations (with shape
[numExamples, inputHeight*inputWidth*numChannels]) for use in feed forward layer
(a) Reshapes epsilons (weights*deltas) out of FeedFoward layer (which is 2D or 3D with shape
[numExamples, inputHeight*inputWidth*numChannels]) into 4d epsilons (with shape
[numExamples, numChannels, inputHeight, inputWidth]) suitable to feed into CNN layers.
Note: numChannels is equivalent to depth or featureMaps referenced in different literature
- CnnToFeedForwardPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- CnnToFeedForwardPreProcessor(int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- CnnToFeedForwardPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- col - Variable in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- combination(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the combination of n choose r
- combineColumns(int, Integer[]) - Method in class org.deeplearning4j.util.StringGrid
-
Combine the column based on a template and a number of template variable
columns.
- combineColumns(int, int[]) - Method in class org.deeplearning4j.util.StringGrid
-
Combine the column based on a template and a number of template variable
columns.
- COMMA - Static variable in class org.deeplearning4j.util.StringUtils
-
- compare(Pair<F, S>, Pair<F, S>) - Method in class org.deeplearning4j.berkeley.Pair.DefaultLexicographicPairComparator
-
- compare(Pair<S, T>, Pair<S, T>) - Method in class org.deeplearning4j.berkeley.Pair.FirstComparator
-
- compare(Pair<F, S>, Pair<F, S>) - Method in class org.deeplearning4j.berkeley.Pair.LexicographicPairComparator
-
- compare(Pair<S, T>, Pair<S, T>) - Method in class org.deeplearning4j.berkeley.Pair.ReverseFirstComparator
-
- compare(Pair<S, T>, Pair<S, T>) - Method in class org.deeplearning4j.berkeley.Pair.ReverseSecondComparator
-
- compare(Pair<S, T>, Pair<S, T>) - Method in class org.deeplearning4j.berkeley.Pair.SecondComparator
-
- compare(Map<String, Integer>, Map<String, Integer>) - Method in class org.deeplearning4j.util.StringCluster.SizeComparator
-
- compareTo(Pair<F, S>) - Method in class org.deeplearning4j.berkeley.Pair
-
Compares this object with the specified object for order.
- compareTo(HeapItem) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- ComposableInputPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
Composable input pre processor
- ComposableInputPreProcessor(InputPreProcessor[]) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- ComposableIterationListener - Class in org.deeplearning4j.optimize.listeners
-
A group of listeners
- ComposableIterationListener(IterationListener...) - Constructor for class org.deeplearning4j.optimize.listeners.ComposableIterationListener
-
- ComposableIterationListener(Collection<IterationListener>) - Constructor for class org.deeplearning4j.optimize.listeners.ComposableIterationListener
-
- ComposableOverride - Class in org.deeplearning4j.nn.conf.override
-
Configuration override
- ComposableOverride(ConfOverride...) - Constructor for class org.deeplearning4j.nn.conf.override.ComposableOverride
-
- computeClusterInfos(Cluster, String) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- computeClusterSetInfo(ClusterSet) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- computeClusterSetInfo(ClusterSet, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- computeDeltas2() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- computeDeltasR(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- computeEdgeForces(INDArray, INDArray, INDArray, int, INDArray) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- computeEdgeForces(INDArray, INDArray, INDArray, int, INDArray) - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
Compute edge forces using barns hut
- computeGaussianKernel(INDArray, double, int) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Computes a gaussian kernel
given a vector of squared distance distances
- computeGaussianPerplexity(INDArray, double) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Convert data to probability
co-occurrences (aka calculating the kernel)
- computeGaussianPerplexity(INDArray, double) - Method in class org.deeplearning4j.plot.Tsne
-
Convert data to probability
co-occurrences (aka calculating the kernel)
- computeGradientAndScore() - Method in interface org.deeplearning4j.nn.api.Model
-
Update the score
- computeGradientAndScore() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- computeGradientAndScore() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- computeGradientAndScore() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- computeGradientAndScore() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- computeGradientAndScore() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- computeGradientAndScore() - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
- computeGradientAndScore() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- computeGradientAndScore() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- computeHistogramBucketIndex(double, double, double, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- computeNonEdgeForces(int, double, INDArray, AtomicDouble) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
Compute non edge forces using barnes hut
- computeNonEdgeForces(int, double, INDArray, AtomicDouble) - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
Compute non edge forces using barnes hut
- computeScore(double, double) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Compute score after labels and input have been set.
- computeSquareDistancesFromNearestCluster(ClusterSet, List<Point>, INDArray, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- computeZ(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
* Compute input linear transformation (z) of the output layer
- computeZ(INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute activations from input to output of the output layer
- concat(Iterable<Iterator<? extends T>>) - Static method in class org.deeplearning4j.berkeley.Iterators
-
- concat(Iterator<? extends T>...) - Static method in class org.deeplearning4j.berkeley.Iterators
-
- concat(Iterable<T>, Iterable<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
-
- concurrentSkipListSet() - Static method in class org.deeplearning4j.util.MultiDimensionalSet
-
- conf() - Method in interface org.deeplearning4j.nn.api.Model
-
The configuration for the neural network
- conf - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- conf() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- conf() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- conf - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- conf() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- configure(NeuralNetConfiguration) - Method in class org.deeplearning4j.optimize.Solver.Builder
-
- ConfOverride - Interface in org.deeplearning4j.nn.conf.override
-
Deprecated.
- confOverrides - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
Deprecated.
- confs - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- confs(List<NeuralNetConfiguration>) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- confs - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- ConfusionMatrix<T extends Comparable<? super T>> - Class in org.deeplearning4j.eval
-
- ConfusionMatrix(List<T>) - Constructor for class org.deeplearning4j.eval.ConfusionMatrix
-
Creates an empty confusion Matrix
- ConfusionMatrix() - Constructor for class org.deeplearning4j.eval.ConfusionMatrix
-
- ConfusionMatrix(ConfusionMatrix<T>) - Constructor for class org.deeplearning4j.eval.ConfusionMatrix
-
Creates a new ConfusionMatrix initialized with the contents of another ConfusionMatrix.
- conjGradient(INDArray, INDArray, INDArray, int) - Method in class org.deeplearning4j.optimize.solvers.StochasticHessianFree
-
- ConjugateGradient - Class in org.deeplearning4j.optimize.solvers
-
Originally based on cc.mallet.optimize.ConjugateGradient
Rewritten based on Conjugate Gradient algorithm in Bengio et al.,
Deep Learning (in preparation) Ch8.
- ConjugateGradient(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.ConjugateGradient
-
- ConjugateGradient(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.ConjugateGradient
-
- connect(List<Tree>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Connects the given trees
and sets the parents of the children
- constrainGradientToUnitNorm(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- constrainGradientToUnitNorm - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- contains(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- contains(double) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect.Interval
-
- contains(INDArray) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- contains(Object) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- contains(K, T) - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
- contains(Object) - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Returns true if this applyTransformToDestination contains the specified element.
- contains(K, V) - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
- containsAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- containsAll(Collection<?>) - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Returns true if this applyTransformToDestination contains all of the elements of the
specified collection.
- containsKey(E) - Method in class org.deeplearning4j.berkeley.Counter
-
Returns whether the counter contains the given key.
- containsKey(K) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- containsKey(Object) - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
Returns true if this map contains a mapping for the specified
key.
- containsPoint(INDArray) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
Whether the given point is contained
within this cell
- containsValue(Object) - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
Returns true if this map maps one or more keys to the
specified value.
- contrastiveDivergence() - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
Contrastive divergence revolves around the idea
of approximating the log likelihood around x1(input) with repeated sampling.
- ConvergenceCondition - Class in org.deeplearning4j.clustering.algorithm.condition
-
- ConvergenceCondition(Condition, double) - Constructor for class org.deeplearning4j.clustering.algorithm.condition.ConvergenceCondition
-
- convertListPairs(List<DataSet>) - Method in class org.deeplearning4j.base.LFWLoader
-
- ConvexOptimizer - Interface in org.deeplearning4j.optimize.api
-
Convex optimizer.
- ConvolutionLayer - Class in org.deeplearning4j.nn.conf.layers
-
- ConvolutionLayer - Class in org.deeplearning4j.nn.layers.convolution
-
Convolution layer
- ConvolutionLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- ConvolutionLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- ConvolutionLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- ConvolutionLayer.PoolingType - Enum in org.deeplearning4j.nn.conf.layers
-
- ConvolutionLayerFactory - Class in org.deeplearning4j.nn.layers.factory
-
Create a convolution layer
- ConvolutionLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.ConvolutionLayerFactory
-
- ConvolutionParamInitializer - Class in org.deeplearning4j.nn.params
-
Initialize convolution params.
- ConvolutionParamInitializer() - Constructor for class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- convolutionType(Convolution.Type) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- convolutionType - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- ConvolutionUtils - Class in org.deeplearning4j.util
-
Convolutional shape utilities
- ConvolutionUtils() - Constructor for class org.deeplearning4j.util.ConvolutionUtils
-
- coordSplit(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the coordinate split in a list of coordinates
such that the values for ret[0] are the x values
and ret[1] are the y values
- coordSplit(List<Double>) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the coordinate split in a list of coordinates
such that the values for ret[0] are the x values
and ret[1] are the y values
- corner(int) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- corner() - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- correlation(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Returns the correlation coefficient of two double vectors.
- corruptionLevel(double) - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder.Builder
-
- corruptionLevel - Variable in class org.deeplearning4j.nn.conf.layers.AutoEncoder
-
- count(V, V) - Method in interface org.deeplearning4j.berkeley.CounterMap.CountFunction
-
- Counter<E> - Class in org.deeplearning4j.berkeley
-
A map from objects to doubles.
- Counter() - Constructor for class org.deeplearning4j.berkeley.Counter
-
- Counter(boolean) - Constructor for class org.deeplearning4j.berkeley.Counter
-
- Counter(MapFactory<E, Double>) - Constructor for class org.deeplearning4j.berkeley.Counter
-
- Counter(Map<? extends E, Double>) - Constructor for class org.deeplearning4j.berkeley.Counter
-
- Counter(Counter<? extends E>) - Constructor for class org.deeplearning4j.berkeley.Counter
-
- Counter(Collection<? extends E>) - Constructor for class org.deeplearning4j.berkeley.Counter
-
- CounterMap<K,V> - Class in org.deeplearning4j.berkeley
-
Maintains counts of (key, value) pairs.
- CounterMap(CounterMap<K, V>) - Constructor for class org.deeplearning4j.berkeley.CounterMap
-
- CounterMap() - Constructor for class org.deeplearning4j.berkeley.CounterMap
-
- CounterMap(MapFactory<K, Counter<V>>, MapFactory<V, Double>) - Constructor for class org.deeplearning4j.berkeley.CounterMap
-
- CounterMap(boolean) - Constructor for class org.deeplearning4j.berkeley.CounterMap
-
- CounterMap.CountFunction<V> - Interface in org.deeplearning4j.berkeley
-
- create() - Method in interface org.deeplearning4j.datasets.creator.DataSetIteratorFactory
-
Create a dataset iterator
- create(NeuralNetConfiguration, int, int, Collection<IterationListener>) - Method in interface org.deeplearning4j.nn.api.LayerFactory
-
Create a layer based on the based in configuration
and an added context.
- create(NeuralNetConfiguration) - Method in interface org.deeplearning4j.nn.api.LayerFactory
-
Create a layer based on the based in configuration
- create(NeuralNetConfiguration, Collection<IterationListener>, int) - Method in interface org.deeplearning4j.nn.api.LayerFactory
-
Create a layer based on the based in configuration
- create(NeuralNetConfiguration, int, int, Collection<IterationListener>) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
-
- create(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
-
- create(NeuralNetConfiguration, Collection<IterationListener>, int) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
-
- createAppendingOutputStream(File) - Static method in class org.deeplearning4j.util.FileOperations
-
- createBias(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- createBias(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- createDistribution(Distribution) - Static method in class org.deeplearning4j.nn.conf.distribution.Distributions
-
- createGradient(INDArray...) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
Create a gradient list based on the passed in parameters.
- createGradient(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- createInputMatrix(int) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
Creates a feature vector
- createOutputMatrix(int) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- createOutputVector(int) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
Creates an output label matrix
- createRandom(Random) - Static method in class org.deeplearning4j.nn.conf.rng.Randoms
-
Deprecated.
Static method for instantiating an nd4j random number generator from a configuration object.
- createStepFunction(StepFunction) - Static method in class org.deeplearning4j.optimize.stepfunctions.StepFunctions
-
- createWeightMatrix(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- createWeightMatrix(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- CSVDataFetcher - Class in org.deeplearning4j.datasets.fetchers
-
Deprecated.
- CSVDataFetcher(InputStream, int) - Constructor for class org.deeplearning4j.datasets.fetchers.CSVDataFetcher
-
Deprecated.
Constructs a csv data fetcher with the specified label column
skipping no lines
- CSVDataFetcher(File, int) - Constructor for class org.deeplearning4j.datasets.fetchers.CSVDataFetcher
-
Deprecated.
Constructs a csv data fetcher with the specified
label column skipping no lines
- CSVDataFetcher(InputStream, int, int) - Constructor for class org.deeplearning4j.datasets.fetchers.CSVDataFetcher
-
Deprecated.
Constructs a csv data fetcher with the specified number of lines to skip
- CSVDataFetcher(File, int, int) - Constructor for class org.deeplearning4j.datasets.fetchers.CSVDataFetcher
-
Deprecated.
Constructs a csv data fetcher with the specified number of lines to skip
- CSVDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
Deprecated.
- CSVDataSetIterator(int, int, InputStream, int) - Constructor for class org.deeplearning4j.datasets.iterator.CSVDataSetIterator
-
Deprecated.
- CSVDataSetIterator(int, int, File, int) - Constructor for class org.deeplearning4j.datasets.iterator.CSVDataSetIterator
-
Deprecated.
- CSVDataSetIterator(int, int, InputStream, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.CSVDataSetIterator
-
Deprecated.
- CSVDataSetIterator(int, int, File, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.CSVDataSetIterator
-
Deprecated.
- curr - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- cursor() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- cursor - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- cursor() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- cursor() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
Direct access to a number represenative of iterating through a dataset
- cursor() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
The current cursor if applicable
- cursor() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
The current cursor if applicable
- cursor() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- CURVES_FILE_NAME - Static variable in class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher
-
- CURVES_URL - Static variable in class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher
-
- CurvesDataFetcher - Class in org.deeplearning4j.datasets.fetchers
-
Curves data fetcher
- CurvesDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher
-
- CurvesDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
Curves data applyTransformToDestination iterator
- CurvesDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.CurvesDataSetIterator
-
- customLossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- customLossFunction(String) - Method in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- customLossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer
-
- customLossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- customLossFunction(String) - Method in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- customLossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
-
- f1(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate f1 score for a given class
- f1() - Method in class org.deeplearning4j.eval.Evaluation
-
TP: true positive
FP: False Positive
FN: False Negative
F1 score: 2 * TP / (2TP + FP + FN)
- f1Score(DataSet) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Sets the input and labels and returns a score for the prediction
wrt true labels
- f1Score(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Returns the f1 score for the given examples.
- f1Score(DataSet) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Sets the input and labels and returns a score for the prediction
wrt true labels
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Returns the f1 score for the given examples.
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
Returns the f1 score for the given examples.
- f1Score(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Sets the input and labels and returns a score for the prediction
wrt true labels
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Sets the input and labels and returns a score for the prediction
wrt true labels
- factorial(double) - Static method in class org.deeplearning4j.util.MathUtils
-
This will return the factorial of the given number n.
- Factory<T> - Interface in org.deeplearning4j.berkeley
-
- Factory.DefaultFactory<T> - Class in org.deeplearning4j.berkeley
-
- FACTORY_KEY - Static variable in interface org.deeplearning4j.datasets.creator.DataSetIteratorFactory
-
- falseNegatives() - Method in class org.deeplearning4j.eval.Evaluation
-
False negatives: correctly rejected
- falsePositives() - Method in class org.deeplearning4j.eval.Evaluation
-
False positive: wrong guess
- feedForward(INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute activations from input to output of the output layer
- feedForward(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute activations from input to output of the output layer
- feedForward() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute activations from input to output of the output layer
- feedForward(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute activations from input to output of the output layer
- feedForwardActivationsAndDerivatives(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute input linear transformation (z)
Compute activations (applies activation transformation to z)
- FeedForwardLayer - Class in org.deeplearning4j.nn.conf.layers
-
Created by jeffreytang on 7/21/15.
- FeedForwardLayer(FeedForwardLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- FeedForwardLayer.Builder<T extends FeedForwardLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- feedForwardR(List<INDArray>, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Feed forward with the r operator
- feedForwardR(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Feed forward with the r operator
- FeedForwardToCnnPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow CNN and standard feed-forward network layers to be used together.
For example, DenseLayer -> CNN
This does two things:
(a) Reshapes activations out of FeedFoward layer (which is 2D or 3D with shape
[numExamples, inputHeight*inputWidth*numChannels]) into 4d activations (with shape
[numExamples, numChannels, inputHeight, inputWidth]) suitable to feed into CNN layers.
(b) Reshapes 4d epsilons (weights*deltas) from CNN layer, with shape
[numExamples, numChannels, inputHeight, inputWidth]) into 2d epsilons (with shape
[numExamples, inputHeight*inputWidth*numChannels]) for use in feed forward layer
Note: numChannels is equivalent to depth or featureMaps referenced in different literature
- FeedForwardToCnnPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
Reshape to a channels x rows x columns tensor
- FeedForwardToCnnPreProcessor(int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- FeedForwardToRnnPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow RNN and feed-forward network layers to be used together.
For example, DenseLayer -> GravesLSTM
This does two things:
(a) Reshapes activations out of FeedFoward layer (which is 2D with shape
[miniBatchSize*timeSeriesLength,layerSize]) into 3d activations (with shape
[miniBatchSize,layerSize,timeSeriesLength]) suitable to feed into RNN layers.
(b) Reshapes 3d epsilons (weights*deltas from RNN layer, with shape
[miniBatchSize,layerSize,timeSeriesLength]) into 2d epsilons (with shape
[miniBatchSize*timeSeriesLength,layerSize]) for use in feed forward layer
- FeedForwardToRnnPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.CSVDataFetcher
-
Deprecated.
Fetches the next dataset.
- fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher
-
Fetches the next dataset.
- fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
-
- fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
-
- fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- fetch(int) - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
Fetches the next dataset.
- fetch(int) - Method in class org.deeplearning4j.datasets.iterator.impl.MovingWindowDataSetFetcher
-
Fetches the next dataset.
- fetcher - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- fileNameClean(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns a "clean" version of the given filename in which spaces have
been converted to dashes and all non-alphaneumeric chars are underscores.
- FileOperations - Class in org.deeplearning4j.util
-
- fillDown(String, int) - Method in class org.deeplearning4j.util.StringGrid
-
- fillList(Iterator<? extends T>, List<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
-
- fillList(Iterator<? extends T>) - Static method in class org.deeplearning4j.berkeley.Iterators
-
- Filter<T> - Interface in org.deeplearning4j.berkeley
-
Filters are boolean cooccurrences which accept or reject items.
- filter(Iterator<T>, Filter<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
-
- filterBySimilarity(double, int, int) - Method in class org.deeplearning4j.util.StringGrid
-
- FilteredIterator(Filter<T>, Iterator<T>) - Constructor for class org.deeplearning4j.berkeley.Iterators.FilteredIterator
-
- FilteredIterator(Filter<T>, Iterable<T>) - Constructor for class org.deeplearning4j.berkeley.Iterators.FilteredIterator
-
- FilterPanel - Class in org.deeplearning4j.plot
-
- FilterPanel(BufferedImage) - Constructor for class org.deeplearning4j.plot.FilterPanel
-
- FilterRenderer - Class in org.deeplearning4j.plot
-
Deprecated.
- FilterRenderer() - Constructor for class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- filterRowsByColumn(int, Collection<String>) - Method in class org.deeplearning4j.util.StringGrid
-
- finalMomentum - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- finalMomentum - Variable in class org.deeplearning4j.plot.Tsne
-
- find(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Say whether this regular expression can be found inside
this String.
- findIndex(INDArray) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
Returns the cell of this element
- findNext(String, char, char, int, StringBuilder) - Static method in class org.deeplearning4j.util.StringUtils
-
Finds the first occurrence of the separator character ignoring the escaped
separators starting from the index.
- finetune() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Run SGD based on the given labels
- FingerPrintKeyer - Class in org.deeplearning4j.util
-
Copied from google refine:
takes the key and gets rid of all punctuation, transforms to lower case
and alphabetic sorts the words
- FingerPrintKeyer() - Constructor for class org.deeplearning4j.util.FingerPrintKeyer
-
- firstChild() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- FirstComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.FirstComparator
-
- fit(DataSetIterator) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Train the model based on the datasetiterator
- fit(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Fit the model
- fit(DataSet) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Fit the model
- fit(INDArray, int[]) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Fit the model
- fit() - Method in interface org.deeplearning4j.nn.api.Model
-
All models have a fit method
- fit(INDArray) - Method in interface org.deeplearning4j.nn.api.Model
-
Fit the model to the given data
- fit(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.api.SequenceClassifier
-
- fit() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- fit(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- fit(DataSetIterator) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Fit the model
- fit(DataSet) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Fit the model
- fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Fit the model
- fit(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Fit the model to the given data
- fit(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- fit() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- fit(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- fit(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.dense.DenseLayer
-
- fit(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
Note: k is the first input hidden params.
- fit(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- fit(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Fit the model
- fit(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Fit the unsupervised model
- fit(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Fit the model
- fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Fit the model
- fit() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- fit() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- fit(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- fit(INDArray, int) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- FixedClusterCountStrategy - Class in org.deeplearning4j.clustering.algorithm.strategy
-
- FixedClusterCountStrategy(Integer, String, boolean) - Constructor for class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
-
- FixedIterationCountCondition - Class in org.deeplearning4j.clustering.algorithm.condition
-
- FixedIterationCountCondition(int) - Constructor for class org.deeplearning4j.clustering.algorithm.condition.FixedIterationCountCondition
-
- flattenedImageFromFile(File) - Method in class org.deeplearning4j.util.ImageLoader
-
- formatPercent(double, int) - Static method in class org.deeplearning4j.util.StringUtils
-
Format a percentage for presentation to the user.
- formatTime(long) - Static method in class org.deeplearning4j.util.StringUtils
-
Given the time in long milliseconds, returns a
String in the format Xhrs, Ymins, Z sec.
- formatTimeDiff(long, long) - Static method in class org.deeplearning4j.util.StringUtils
-
Given a finish and start time in long milliseconds, returns a
String in the format Xhrs, Ymins, Z sec, for the time difference between two times.
- frame - Variable in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
-
- frame - Variable in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- fromFile(File) - Method in class org.deeplearning4j.util.ImageLoader
-
- fromFile(String, String) - Static method in class org.deeplearning4j.util.StringGrid
-
- fromImageFile(int, File) - Method in class org.deeplearning4j.base.LFWLoader
-
- fromInput(InputStream, String) - Static method in class org.deeplearning4j.util.StringGrid
-
- fromJson(String) - Static method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
Create a neural net configuration from json
- fromJson(String) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Create a neural net configuration from json
- fromString(String, String) - Static method in class org.deeplearning4j.util.MathUtils
-
This will take a given string and separator and convert it to an equivalent
double array.
- fromYaml(String) - Static method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
Create a neural net configuration from json
- fromYaml(String) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Create a neural net configuration from json
- gains - Variable in class org.deeplearning4j.plot.Tsne
-
- generateHistogramBuckets(INDArray, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
Take some matrix input data and a bucket count and compute:
- a list of N buckets, each with:
1.
- generateUniform(int) - Static method in class org.deeplearning4j.util.MathUtils
-
This will generate a series of uniformally distributed
numbers between l times
- get(int) - Method in class org.deeplearning4j.util.Index
-
- get(Object) - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
Returns the value to which the specified key is mapped,
or null if this map contains no mapping for the key.
- get(K, T) - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
- getAccumulation() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getActualTotal(T) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Computes the total number of times the class actually appeared in the data.
- getAllFields(Class<?>) - Static method in class org.deeplearning4j.util.Dl4jReflection
-
- getAllImagesAsMatrix() - Method in class org.deeplearning4j.base.LFWLoader
-
- getAllImagesAsMatrix(int) - Method in class org.deeplearning4j.base.LFWLoader
-
- getAllWithSimilarity(double, int, int) - Method in class org.deeplearning4j.util.StringGrid
-
- getArray() - Method in class org.deeplearning4j.clustering.cluster.Point
-
- getAveragePointDistanceFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- getAveragePointDistanceFromClusterCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- getBackPropGradient2() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Gets the back prop gradient with the r operator (gauss vector)
and the associated precon matrix
This is also called computeGV
- getBackPropRGradient(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Gets the back prop gradient with the r operator (gauss vector)
This is also called computeGV
- getBegin() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- getBoundary() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getBoundary() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getCenter() - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- getCenter() - Method in class org.deeplearning4j.clustering.Cluster
-
- getCenterOfMass() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getCenterOfMass() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getCenters() - Method in class org.deeplearning4j.clustering.ClusterSet
-
- getChildren() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getChildren() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- getClass(T) - Static method in class org.deeplearning4j.util.ReflectionUtils
-
Return the correctly-typed
Class of the given object.
- getClasses() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Gives the applyTransformToDestination of all classes in the confusion matrix.
- getCluster(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getCluster() - Method in class org.deeplearning4j.clustering.cluster.PointClassification
-
- getClusterCenter(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getClusterCenterId(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getClusterCount() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getClusterCount() - Method in class org.deeplearning4j.clustering.ClusterSet
-
- getClusterInfo(String) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- getClusteringOptimizationValue() - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
-
- getClusters() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getClusters() - Method in class org.deeplearning4j.clustering.ClusterSet
-
- getClusters() - Method in class org.deeplearning4j.util.StringCluster
-
- getClusterSetInfo() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
-
- getClustersInfos() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- getClustersWhereAverageDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- getClustersWhereMaximumDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- getCols() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Number of columns per image.
- getColumn(int) - Method in class org.deeplearning4j.util.StringGrid
-
- getConf(int) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- getCorruptedInput(INDArray, double) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
Corrupts the given input by doing a binomial sampling
given the corruption level
- getCount(E) - Method in class org.deeplearning4j.berkeley.Counter
-
Get the count of the element, or zero if the element is not in the
counter.
- getCount(K, V) - Method in class org.deeplearning4j.berkeley.CounterMap
-
Gets the count of the given (key, value) entry, or zero if that entry is
not present.
- getCount(K) - Method in class org.deeplearning4j.berkeley.CounterMap
-
Gets the total count of the given key, or zero if that key is
not present.
- getCount() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
- getCount(T, T) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Gives the count of the number of times the "predicted" class was predicted for the "actual"
class.
- getCounter(K) - Method in class org.deeplearning4j.berkeley.CounterMap
-
Gets the sub-counter for the given key.
- getCounters() - Method in class org.deeplearning4j.berkeley.CounterMap
-
- getCumSize() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getCumSize() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getCurrentIndex() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
The current entry index.
- getD() - Method in class org.deeplearning4j.clustering.sptree.DataPoint
-
- getD() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getDataFor(int) - Method in class org.deeplearning4j.base.LFWLoader
-
- getDefaultStepFunctionForOptimizer(Class<? extends ConvexOptimizer>) - Static method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- getDeflt() - Method in class org.deeplearning4j.berkeley.Counter
-
- getDistance(Point, Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getDistance() - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- getDistanceFromCenter() - Method in class org.deeplearning4j.clustering.cluster.PointClassification
-
- getDistanceFromNearestCluster(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getDistanceFromNearestCluster(INDArray) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- getDistanceFunction() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- getDistanceFunction() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
-
- getDistanceFunction() - Method in class org.deeplearning4j.clustering.ClusterSet
-
- getDistances() - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
- getDistancesBetweenClustersCenters() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- getDistanceToCenter(Point) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- getEmptyConstructor(Class<?>) - Static method in class org.deeplearning4j.util.Dl4jReflection
-
Gets the empty constructor from a class
- getEnd() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- getEntryLength() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Number of bytes for each entry.
- getEntryLength() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
- getEntrySet() - Method in class org.deeplearning4j.berkeley.Counter
-
- getEntrySet() - Method in class org.deeplearning4j.berkeley.CounterMap
-
- getFactory(NeuralNetConfiguration) - Static method in class org.deeplearning4j.nn.layers.factory.LayerFactories
-
Get the factory based on the passed in class
- getFactory(Layer) - Static method in class org.deeplearning4j.nn.layers.factory.LayerFactories
-
Get the factory based on the passed in class
- getFeatureMatrix(int) - Method in class org.deeplearning4j.base.LFWLoader
-
Get the first num found images
- getFieldsAsProperties(Object, Class<?>[]) - Static method in class org.deeplearning4j.util.Dl4jReflection
-
Get fields as properties
- getFilters() - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- getFirst() - Method in class org.deeplearning4j.berkeley.Pair
-
- getFirst() - Method in class org.deeplearning4j.berkeley.Triple
-
- getFirstKey() - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
-
- getFormattedTimeWithDiff(DateFormat, long, long) - Static method in class org.deeplearning4j.util.StringUtils
-
Formats time in ms and appends difference (finishTime - startTime)
as returned by formatTimeDiff().
- getGradientFor(String) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- getGradientFor(String) - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
The gradient for the given variable
- getHeaderSize() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
- getHeaderSize() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
- getHeadWord() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- getHeightAndWidth(NeuralNetConfiguration) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Get the height and width
from the configuration
- getHeightAndWidth(int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Get the height and width
for an image
- getHh() - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- getHostname() - Static method in class org.deeplearning4j.util.StringUtils
-
Return hostname without throwing exception.
- getHw() - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- getId() - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- getId() - Method in class org.deeplearning4j.clustering.cluster.Point
-
- getIfNotExists() - Method in class org.deeplearning4j.base.LFWLoader
-
- getImage() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
-
- getImage() - Method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- getImages(int, File) - Method in class org.deeplearning4j.base.LFWLoader
-
- getImages() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
- getImagesAsList() - Method in class org.deeplearning4j.base.LFWLoader
-
- getIndex() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
-
- getIndex() - Method in class org.deeplearning4j.clustering.sptree.DataPoint
-
- getIndex() - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- getIndex() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getIndex() - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- getIndex() - Method in interface org.deeplearning4j.nn.api.Layer
-
Get the layer index.
- getIndex() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- getIndex() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getInitialClusterCount() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- getInitialClusterCount() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
-
- getInput() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- getInput() - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- getInput() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getInput() - Method in class org.deeplearning4j.plot.PlotFilters
-
- getInputMiniBatchSize() - Method in interface org.deeplearning4j.nn.api.Layer
-
Get current/last input mini-batch size, as set by setInputMiniBatchSize(int)
- getInputMiniBatchSize() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- getInputMiniBatchSize() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getInputPreProcess(int) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- getInstance(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
-
- getItems() - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
- getIteration() - Method in class org.deeplearning4j.plot.iterationlistener.ActivationMeanIterationListener
-
- getIteration() - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- getIterationCount() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
-
- getIterationInfo(int) - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
-
- getIterationListener() - Method in class org.deeplearning4j.plot.Tsne
-
- getIterationsInfos() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
-
- getKey() - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
-
Returns the key corresponding to this entry.
- getLabel() - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- getLabel() - Method in class org.deeplearning4j.clustering.cluster.Point
-
- getLabels() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
- getLabels() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- getLabels() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLabels2d() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- getLabels2d() - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- getLayer(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLayerGraphFilePath() - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- getLayers() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLayerWiseConfigurations() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLeaves() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Gets the leaves of the tree.
- getLeaves(List<T>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Gets the leaves of the tree.
- getLeft() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- getLeft() - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- getListeners() - Method in interface org.deeplearning4j.nn.api.Layer
-
Get the iteration listeners for this layer.
- getListeners() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- getListeners() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLogMetaInstability() - Method in class org.deeplearning4j.util.Viterbi
-
- getLogOfDiangnalTProb() - Method in class org.deeplearning4j.util.Viterbi
-
- getLogPCorrect() - Method in class org.deeplearning4j.util.Viterbi
-
- getLogPIncorrect() - Method in class org.deeplearning4j.util.Viterbi
-
- getLogStates() - Method in class org.deeplearning4j.util.Viterbi
-
- getLower(INDArray, int) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- getLower() - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- getMagicNumber() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
MNIST DB files start with unique integer number.
- getMagicNumber() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
- getMagicNumber() - Method in class org.deeplearning4j.datasets.mnist.MnistLabelFile
-
- getMask() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getMax() - Method in class org.deeplearning4j.util.SummaryStatistics
-
- getMaxIterations() - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- getMaxPointDistanceFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- getMean() - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- getMean() - Method in class org.deeplearning4j.util.SummaryStatistics
-
- getMetaStability() - Method in class org.deeplearning4j.util.Viterbi
-
- getMin() - Method in class org.deeplearning4j.util.SummaryStatistics
-
- getMostPopulatedClusters(int) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getMostRecentClusterSetInfo() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
-
- getMostRecentIterationInfo() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
-
- getMostSpreadOutClusters(ClusterSet, ClusterSetInfo, int) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- getnLayers() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Get the number of layers in the network
- getNorthEast() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getNorthWest() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getNumberOfTrials() - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
- getNumChildren() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getNumColumns() - Method in class org.deeplearning4j.util.StringGrid
-
- getNumDataSets() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- getNumNames() - Method in class org.deeplearning4j.base.LFWLoader
-
- getNumPixelColumns() - Method in class org.deeplearning4j.base.LFWLoader
-
- getNumRowCounter() - Method in class org.deeplearning4j.eval.Evaluation
-
- getOptimizationPhaseCondition() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- getOptimizer() - Method in interface org.deeplearning4j.nn.api.Model
-
Returns this models optimizer
- getOptimizer() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- getOptimizer() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getOptimizer() - Method in class org.deeplearning4j.optimize.Solver
-
- getOptimizer() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getOutputFile() - Method in class org.deeplearning4j.plot.iterationlistener.ActivationMeanIterationListener
-
- getOutputFile() - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- getOutputLayer() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Get the output layer
- getPairIterator() - Method in class org.deeplearning4j.berkeley.CounterMap
-
- getParam(String) - Method in interface org.deeplearning4j.nn.api.Model
-
Get the parameter
- getParam(String) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- getParam(String) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getParam(String) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
-
- getParent() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- getParent() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getpCorrect() - Method in class org.deeplearning4j.util.Viterbi
-
- getPerplexity() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getPlot() - Method in class org.deeplearning4j.plot.PlotFilters
-
- getPoint(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- getPoint() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- getPoint() - Method in class org.deeplearning4j.clustering.sptree.DataPoint
-
- getPointDistanceFromCenterVariance() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- getPointDistanceFromClusterVariance() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- getPointDistancesFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- getPointDistribution() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getPointLocationChange() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- getPoints() - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- getPoints() - Method in class org.deeplearning4j.clustering.Cluster
-
- getPointsCount() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- getPointsFartherFromCenterThan(double) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- getPossibleLabels() - Method in class org.deeplearning4j.util.Viterbi
-
- getPredictedTotal(T) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Computes the total number of times the class was predicted by the classifier.
- getPriority() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- getPriority() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface
-
Gets the priority of the highest-priority element of the queue.
- getProbability(E) - Method in class org.deeplearning4j.berkeley.Counter
-
I know, I know, this should be wrapped in a Distribution class, but it's
such a common use...why not.
- getProbabilityOfSuccess() - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
- getReverseSortedPointDistancesFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- getRight() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- getRight() - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- getRow(int) - Method in class org.deeplearning4j.util.StringGrid
-
- getRows() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Number of rows per image.
- getRowsWithColumnValues(Collection<String>, int) - Method in class org.deeplearning4j.util.StringGrid
-
- getRowsWithDuplicateValuesInColumn(int) - Method in class org.deeplearning4j.util.StringGrid
-
- getRowWithOnlyOneOccurrence(int) - Method in class org.deeplearning4j.util.StringGrid
-
- getSecond() - Method in class org.deeplearning4j.berkeley.Pair
-
- getSecond() - Method in class org.deeplearning4j.berkeley.Triple
-
- getSecondKey() - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
-
- getSeed() - Method in class org.deeplearning4j.nn.conf.rng.DefaultRandom
-
Deprecated.
- getSimiarlityFunction() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getSize() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getSortedKeys() - Method in class org.deeplearning4j.berkeley.Counter
-
- getSortedPointDistancesFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- getSouthEast() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getSouthWest() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getStates() - Method in class org.deeplearning4j.util.Viterbi
-
- getStd() - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- getStepMax() - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- getStringCollection(String) - Static method in class org.deeplearning4j.util.StringUtils
-
Returns a collection of strings.
- getStrings(String) - Static method in class org.deeplearning4j.util.StringUtils
-
Returns an arraylist of strings.
- getSum() - Method in class org.deeplearning4j.util.SummaryStatistics
-
- getTerminationCondition() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- getTerminationCondition() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
-
- getTheta() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getThird() - Method in class org.deeplearning4j.berkeley.Triple
-
- getThreshold() - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- getTokens() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- getTotalPointDistanceFromCenter() - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- getTrimmedStringCollection(String) - Static method in class org.deeplearning4j.util.StringUtils
-
Splits a comma separated value String, trimming leading and trailing whitespace on each value.
- getTrimmedStrings(String) - Static method in class org.deeplearning4j.util.StringUtils
-
Splits a comma separated value String, trimming leading and trailing whitespace on each value.
- getType() - Method in class org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimization
-
- getType() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- getType() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
-
- getType() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
The type of node; mainly extra meta data
- getUniqueRows() - Method in class org.deeplearning4j.util.StringGrid
-
- getUpdater(Model) - Static method in class org.deeplearning4j.nn.updater.UpdaterCreator
-
- getUpdater() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
- getUpdater() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- getUpper(INDArray, int) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- getUpper() - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- getValue() - Method in class org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimization
-
- getValue() - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
-
- getVariables() - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- getX() - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- getY() - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- getY() - Method in class org.deeplearning4j.plot.Tsne
-
- getYGradient(int, INDArray, INDArray) - Method in class org.deeplearning4j.plot.Tsne
-
- gibbhVh(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
Gibbs sampling step: hidden ---> visible ---> hidden
- goldLabel() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- gr(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
Tests if a is greater than b.
- gradient() - Method in interface org.deeplearning4j.nn.api.Model
-
Calculate a gradient
- gradient(List<String>) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- gradient() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- Gradient - Interface in org.deeplearning4j.nn.gradient
-
Generic gradient
- gradient(List<String>) - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
The full gradient as one flat vector
- gradient() - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
The full gradient as one flat vector
- gradient - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- gradient() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- gradient() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Gets the gradient from one training iteration
- gradient() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- gradient() - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- gradient - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- gradient() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- gradient(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- gradient() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- gradient(INDArray) - Method in class org.deeplearning4j.plot.Tsne
-
- GRADIENT_KEY - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- GradientAdjustment - Class in org.deeplearning4j.optimize
-
Gradient adjustment
- gradientAndScore() - Method in interface org.deeplearning4j.nn.api.Model
-
Get the gradient and score
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- gradientAndScore() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
The gradient and score for this optimizer
- gradientAndScore() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- gradientAndScore() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- GradientCheckUtil - Class in org.deeplearning4j.gradientcheck
-
A utility for numerically checking gradients.
- GradientCheckUtil() - Constructor for class org.deeplearning4j.gradientcheck.GradientCheckUtil
-
- gradientForVariable() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- gradientForVariable() - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
Gradient look up table
- GradientPlotterIterationListener - Class in org.deeplearning4j.plot.iterationlistener
-
Plots weight distributions and activation probabilities
- GradientPlotterIterationListener(int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.GradientPlotterIterationListener
-
- GradientPlotterIterationListener(int, NeuralNetPlotter) - Constructor for class org.deeplearning4j.plot.iterationlistener.GradientPlotterIterationListener
-
- GradientPlotterIterationListener(int, NeuralNetPlotter, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.GradientPlotterIterationListener
-
- GradientPlotterIterationListener(int) - Constructor for class org.deeplearning4j.plot.iterationlistener.GradientPlotterIterationListener
-
- GradientStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions
-
Normal gradient step function
- GradientStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.GradientStepFunction
-
- GradientStepFunction - Class in org.deeplearning4j.optimize.stepfunctions
-
Normal gradient step function
- GradientStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
-
- graphPlotType(String, List<String>, INDArray[], String) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
graphPlotType sets up data to pass to scripts that render graphs
- GravesLSTM - Class in org.deeplearning4j.nn.conf.layers
-
LSTM recurrent net, based on Graves: Supervised Sequence Labelling with Recurrent Neural Networks
http://www.cs.toronto.edu/~graves/phd.pdf
- GravesLSTM - Class in org.deeplearning4j.nn.layers.recurrent
-
LSTM layer implementation.
- GravesLSTM(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- GravesLSTM(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- GravesLSTM.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- GravesLSTMLayerFactory - Class in org.deeplearning4j.nn.layers.factory
-
LSTM layer initializer.
- GravesLSTMLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.GravesLSTMLayerFactory
-
- GravesLSTMParamInitializer - Class in org.deeplearning4j.nn.params
-
LSTM Parameter initializer, for LSTM based on
Graves: Supervised Sequence Labelling with Recurrent Neural Networks
http://www.cs.toronto.edu/~graves/phd.pdf
- GravesLSTMParamInitializer() - Constructor for class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- GREATER - Static variable in class org.deeplearning4j.clustering.kdtree.KDTree
-
- grow(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- GRU - Class in org.deeplearning4j.nn.conf.layers
-
Gated Recurrent Unit RNN Layer.
The GRU was recently proposed by Cho et al.
- GRU - Class in org.deeplearning4j.nn.layers.recurrent
-
Gated Recurrent Unit RNN Layer.
The GRU was recently proposed by Cho et al.
- GRU(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.GRU
-
- GRU(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.GRU
-
- GRU.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- GRULayerFactory - Class in org.deeplearning4j.nn.layers.factory
-
GRU: Gated Recurrent Unit RNN
- GRULayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.GRULayerFactory
-
- GRUParamInitializer - Class in org.deeplearning4j.nn.params
-
- GRUParamInitializer() - Constructor for class org.deeplearning4j.nn.params.GRUParamInitializer
-
- gunzipFile(File, File) - Static method in class org.deeplearning4j.base.MnistFetcher
-
- IdentityHashMapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory.IdentityHashMapFactory
-
- idf(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
Inverse document frequency: the total docs divided by the number of times the word
appeared in a document
- ImageLoader - Class in org.deeplearning4j.util
-
Image loader for taking images and converting them to matrices
- ImageLoader() - Constructor for class org.deeplearning4j.util.ImageLoader
-
- ImageLoader(int, int) - Constructor for class org.deeplearning4j.util.ImageLoader
-
- ImageLSTM - Class in org.deeplearning4j.nn.conf.layers
-
Image LSTM recurrent net.
- ImageLSTM - Class in org.deeplearning4j.nn.layers.recurrent
-
LSTM image recurrent net.
- ImageLSTM(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- ImageLSTM(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- ImageLSTM.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- ImageLSTMLayerFactory - Class in org.deeplearning4j.nn.layers.factory
-
LSTM layer initializer
- ImageLSTMLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.ImageLSTMLayerFactory
-
- ImageLSTMParamInitializer - Class in org.deeplearning4j.nn.params
-
LSTM Parameters.
- ImageLSTMParamInitializer() - Constructor for class org.deeplearning4j.nn.params.ImageLSTMParamInitializer
-
- ImageVectorizer - Class in org.deeplearning4j.datasets.vectorizer
-
An image vectorizer takes an input image (RGB) and
transforms it in to a data applyTransformToDestination
- ImageVectorizer(File, int, int) - Constructor for class org.deeplearning4j.datasets.vectorizer.ImageVectorizer
-
Baseline knowledge needed for the vectorizer
- incrementAll(Collection<? extends E>, double) - Method in class org.deeplearning4j.berkeley.Counter
-
Increment each element in a given collection by a given amount.
- incrementAll(Counter<T>) - Method in class org.deeplearning4j.berkeley.Counter
-
- incrementAll(Map<K, V>, double) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- incrementAll(CounterMap<K, V>) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- incrementCount(E, double) - Method in class org.deeplearning4j.berkeley.Counter
-
Increment a key's count by the given amount.
- incrementCount(K, V, double) - Method in class org.deeplearning4j.berkeley.CounterMap
-
Increments the count for a particular (key, value) pair.
- incrementFalseNegatives(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
- incrementFalsePositives(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
- incrementTrueNegatives(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
- incrementTruePositives(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
- index - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- Index - Class in org.deeplearning4j.util
-
An index is a transform of objects augmented with a list and a reverse lookup table
for fast lookups.
- Index() - Constructor for class org.deeplearning4j.util.Index
-
- indexOf(Object) - Method in class org.deeplearning4j.util.Index
-
- information(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the entropy for a given vector of probabilities.
- init(Map<String, INDArray>, NeuralNetConfiguration) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
Initialize the parameters
- init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
Initialization via extra parameters where necessary
- init() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Initialize
- init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.GRUParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.GRUParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.ImageLSTMParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.ImageLSTMParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.PretrainParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.RecursiveParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.SubsampleParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.SubsampleParamInitializer
-
- init() - Method in class org.deeplearning4j.nn.updater.AdaDeltaUpdater
-
- init(String, INDArray, Layer) - Method in class org.deeplearning4j.nn.updater.AdaDeltaUpdater
-
- init() - Method in class org.deeplearning4j.nn.updater.AdaGradUpdater
-
- init(String, INDArray, Layer) - Method in class org.deeplearning4j.nn.updater.AdaGradUpdater
-
- init() - Method in class org.deeplearning4j.nn.updater.AdamUpdater
-
- init(String, INDArray, Layer) - Method in class org.deeplearning4j.nn.updater.AdamUpdater
-
- init() - Method in class org.deeplearning4j.nn.updater.BaseUpdater
-
- init(String, INDArray, Layer) - Method in class org.deeplearning4j.nn.updater.BaseUpdater
-
- init() - Method in class org.deeplearning4j.nn.updater.NesterovsUpdater
-
- init(String, INDArray, Layer) - Method in class org.deeplearning4j.nn.updater.NesterovsUpdater
-
- init() - Method in class org.deeplearning4j.nn.updater.NoOpUpdater
-
- init(String, INDArray, Layer) - Method in class org.deeplearning4j.nn.updater.NoOpUpdater
-
- init() - Method in class org.deeplearning4j.nn.updater.RmsPropUpdater
-
- init(String, INDArray, Layer) - Method in class org.deeplearning4j.nn.updater.RmsPropUpdater
-
- init() - Method in class org.deeplearning4j.nn.updater.SgdUpdater
-
- init(String, INDArray, Layer) - Method in class org.deeplearning4j.nn.updater.SgdUpdater
-
- initCalled - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- initClusters() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- initialClusterCount - Variable in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- initialize(ClusterSet, boolean) - Static method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- initialize(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Sets the input and labels from this dataset
- initializeCurrFromList(List<DataSet>) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
Initializes this data transform fetcher from the passed in datasets
- initializeLayers(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Base class for initializing the neuralNets based on the input.
- initializer() - Method in interface org.deeplearning4j.nn.api.LayerFactory
-
Get the param initializer used for initializing layers
- initializer() - Method in class org.deeplearning4j.nn.layers.factory.ConvolutionLayerFactory
-
- initializer() - Method in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
-
- initializer() - Method in class org.deeplearning4j.nn.layers.factory.GravesLSTMLayerFactory
-
- initializer() - Method in class org.deeplearning4j.nn.layers.factory.GRULayerFactory
-
- initializer() - Method in class org.deeplearning4j.nn.layers.factory.ImageLSTMLayerFactory
-
- initializer() - Method in class org.deeplearning4j.nn.layers.factory.PretrainLayerFactory
-
- initializer() - Method in class org.deeplearning4j.nn.layers.factory.RecursiveAutoEncoderLayerFactory
-
- initializer() - Method in class org.deeplearning4j.nn.layers.factory.SubsampleLayerFactory
-
- initialMomentum - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- initialMomentum - Variable in class org.deeplearning4j.plot.Tsne
-
- initParams() - Method in interface org.deeplearning4j.nn.api.Model
-
Initialize the parameters
- initParams() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- initParams() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- initParams() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- initWeights(int[], float, float) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil
-
- initWeights(int[], WeightInit, Distribution) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil
-
Initializes a matrix with the given weight initialization scheme
- initWeights(int, int, WeightInit, Distribution) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil
-
Initializes a matrix with the given weight initialization scheme
- input() - Method in interface org.deeplearning4j.nn.api.Model
-
The input/feature matrix for the model
- input - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- input() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- input - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- input() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- input() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- INPUT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- INPUT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.GRUParamInitializer
-
- INPUT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.ImageLSTMParamInitializer
-
- inputColumns() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- inputColumns - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- inputColumns() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- inputColumns() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
The length of a feature vector for an individual example
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Input columns for the dataset
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Input columns for the dataset
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- inputMiniBatchSize - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- InputPreProcessor - Interface in org.deeplearning4j.nn.conf
-
Input pre processor used
for pre processing input before passing it
to the neural network.
- inputPreProcessor(Integer, InputPreProcessor) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
Specify the processors.
- inputPreProcessors - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- inputPreProcessors(Map<Integer, InputPreProcessor>) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- inputPreProcessors - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- InputSplit - Class in org.deeplearning4j.util
-
- InputSplit() - Constructor for class org.deeplearning4j.util.InputSplit
-
- inputStreamFromPath(String) - Static method in class org.deeplearning4j.util.DeepLearningIOUtil
-
- insert(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.KDTree
-
Insert a point in to the tree
- insert(int) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
Insert an index of the data in to the tree
- intersection(Collection<T>, Collection<T>) - Static method in class org.deeplearning4j.util.SetUtils
-
- intersectionP(Set<? extends T>, Set<? extends T>) - Static method in class org.deeplearning4j.util.SetUtils
-
- Interval(double, double) - Constructor for class org.deeplearning4j.clustering.kdtree.HyperRect.Interval
-
- intializeConfigurations() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- intPow(int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
exponentiation like we learned in grade school: multiply b by itself e
times.
- intPow(float, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
exponentiation like we learned in grade school: multiply b by itself e
times.
- intPow(double, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
exponentiation like we learned in grade school: multiply b by itself e
times.
- InvalidStepException - Exception in org.deeplearning4j.exception
-
Created by agibsonccc on 8/20/14.
- InvalidStepException(String) - Constructor for exception org.deeplearning4j.exception.InvalidStepException
-
Constructs a new exception with the specified detail message.
- InvalidStepException(String, Throwable) - Constructor for exception org.deeplearning4j.exception.InvalidStepException
-
Constructs a new exception with the specified detail message and
cause.
- InvalidStepException(Throwable) - Constructor for exception org.deeplearning4j.exception.InvalidStepException
-
Constructs a new exception with the specified cause and a detail
message of (cause==null ? null : cause.toString()) (which
typically contains the class and detail message of cause).
- InvalidStepException(String, Throwable, boolean, boolean) - Constructor for exception org.deeplearning4j.exception.InvalidStepException
-
Constructs a new exception with the specified detail message,
cause, suppression enabled or disabled, and writable stack
trace enabled or disabled.
- inverse(RBM.HiddenUnit) - Static method in class org.deeplearning4j.util.RBMUtil
-
- inverse(RBM.VisibleUnit) - Static method in class org.deeplearning4j.util.RBMUtil
-
- invert() - Method in class org.deeplearning4j.berkeley.CounterMap
-
Constructs reverse CounterMap where the count of a pair (k,v)
is the count of (v,k) in the current CounterMap
- invertDistanceMetric(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- invoke() - Method in interface org.deeplearning4j.optimize.api.IterationListener
-
Change invoke to true
- invoke() - Method in class org.deeplearning4j.optimize.listeners.ComposableIterationListener
-
- invoke() - Method in class org.deeplearning4j.optimize.listeners.ScoreIterationListener
-
- invoke() - Method in class org.deeplearning4j.plot.iterationlistener.AccuracyPlotterIterationListener
-
- invoke() - Method in class org.deeplearning4j.plot.iterationlistener.ActivationMeanIterationListener
-
- invoke() - Method in class org.deeplearning4j.plot.iterationlistener.GradientPlotterIterationListener
-
- invoke() - Method in class org.deeplearning4j.plot.iterationlistener.LossPlotterIterationListener
-
- invoke() - Method in class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
-
- invoke() - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- invoke() - Method in class org.deeplearning4j.plot.iterationlistener.RenderFilterIterationListener
-
- invoked() - Method in interface org.deeplearning4j.optimize.api.IterationListener
-
Get if listener invoked
- invoked() - Method in class org.deeplearning4j.optimize.listeners.ComposableIterationListener
-
- invoked() - Method in class org.deeplearning4j.optimize.listeners.ScoreIterationListener
-
- invoked() - Method in class org.deeplearning4j.plot.iterationlistener.AccuracyPlotterIterationListener
-
- invoked() - Method in class org.deeplearning4j.plot.iterationlistener.ActivationMeanIterationListener
-
- invoked() - Method in class org.deeplearning4j.plot.iterationlistener.GradientPlotterIterationListener
-
- invoked() - Method in class org.deeplearning4j.plot.iterationlistener.LossPlotterIterationListener
-
- invoked() - Method in class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
-
- invoked() - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- invoked() - Method in class org.deeplearning4j.plot.iterationlistener.RenderFilterIterationListener
-
- iris() - Static method in class org.deeplearning4j.datasets.DataSets
-
- iris(int) - Static method in class org.deeplearning4j.datasets.DataSets
-
- IrisDataFetcher - Class in org.deeplearning4j.datasets.fetchers
-
- IrisDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
-
- IrisDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
- IrisDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator
-
IrisDataSetIterator handles
traversing through the Iris Data Set.
- IrisUtils - Class in org.deeplearning4j.base
-
- IrisUtils() - Constructor for class org.deeplearning4j.base.IrisUtils
-
- isAllowEmptyClusters() - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- isAllowEmptyClusters() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
-
- isClusteringOptimizationType(ClusteringOptimizationType) - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
-
- isConverged() - Method in class org.deeplearning4j.optimize.solvers.StochasticHessianFree
-
- isCorrect() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
Returns whether the tree is consistent or not
- isCorrect() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
Verifies the structure of the tree (does bounds checking on each node)
- isDangerous(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Returns true if the argument is a "dangerous" double to have around,
namely one that is infinite, NaN or zero.
- isDangerous(float) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- isDiscreteProb(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- isEmpty() - Method in class org.deeplearning4j.berkeley.Counter
-
True if there are no entries in the counter (false does not mean
totalCount > 0)
- isEmpty() - Method in class org.deeplearning4j.berkeley.CounterMap
-
True if there are no entries in the CounterMap (false does not mean
totalCount > 0)
- isEmpty() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- isEmpty() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface
-
True if the queue is empty (size == 0).
- isEmpty() - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- isEmpty() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- isEmpty() - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
Returns true if this map contains no key-value mappings.
- isEmpty() - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Returns true if this applyTransformToDestination contains no elements.
- isEqualTo(Counter<E>) - Method in class org.deeplearning4j.berkeley.Counter
-
- isEqualTo(CounterMap<K, V>) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- isGreater(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- isInvert() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- isLeaf() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- isLeaf() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- isLeaf() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Returns whether the node has any children or not
- isNewLocation() - Method in class org.deeplearning4j.clustering.cluster.PointClassification
-
- isOptimizationApplicableNow(IterationHistory) - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
-
- isOptimizationApplicableNow(IterationHistory) - Method in class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
-
- isOptimizationApplicableNow(IterationHistory) - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
-
- isOptimizationDefined() - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
-
- isOptimizationDefined() - Method in class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
-
- isOptimizationDefined() - Method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
-
- isPreTerminal() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Node has one child that is a leaf
- isSatisfied(IterationHistory) - Method in interface org.deeplearning4j.clustering.algorithm.condition.ClusteringAlgorithmCondition
-
- isSatisfied(IterationHistory) - Method in class org.deeplearning4j.clustering.algorithm.condition.ConvergenceCondition
-
- isSatisfied(IterationHistory) - Method in class org.deeplearning4j.clustering.algorithm.condition.FixedIterationCountCondition
-
- isSatisfied(IterationHistory) - Method in class org.deeplearning4j.clustering.algorithm.condition.VarianceVariationCondition
-
- isStrategyApplied() - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
-
- isStrategyOfType(ClusteringStrategyType) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- isStrategyOfType(ClusteringStrategyType) - Method in interface org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategy
-
- isVeryDangerous(double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Returns true if the argument is a "very dangerous" double to have around,
namely one that is infinite or NaN.
- iterate(INDArray) - Method in interface org.deeplearning4j.nn.api.Model
-
Run one iteration
- iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
iterate one iteration of the network
- iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- iterate(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
- iterate(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- iterate(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- iteration - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- iterationCountGreaterThan(int) - Static method in class org.deeplearning4j.clustering.algorithm.condition.FixedIterationCountCondition
-
- iterationDone(Model, int) - Method in interface org.deeplearning4j.optimize.api.IterationListener
-
Event listener for each iteration
- iterationDone(Model, int) - Method in class org.deeplearning4j.optimize.listeners.ComposableIterationListener
-
- iterationDone(Model, int) - Method in class org.deeplearning4j.optimize.listeners.ScoreIterationListener
-
- iterationDone(Model, int) - Method in class org.deeplearning4j.plot.iterationlistener.AccuracyPlotterIterationListener
-
- iterationDone(Model, int) - Method in class org.deeplearning4j.plot.iterationlistener.ActivationMeanIterationListener
-
- iterationDone(Model, int) - Method in class org.deeplearning4j.plot.iterationlistener.GradientPlotterIterationListener
-
- iterationDone(Model, int) - Method in class org.deeplearning4j.plot.iterationlistener.LossPlotterIterationListener
-
- iterationDone(Model, int) - Method in class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
-
- iterationDone(Model, int) - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- iterationDone(Model, int) - Method in class org.deeplearning4j.plot.iterationlistener.RenderFilterIterationListener
-
- IterationHistory - Class in org.deeplearning4j.clustering.algorithm.iteration
-
- IterationHistory() - Constructor for class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
-
- IterationInfo - Class in org.deeplearning4j.clustering.algorithm.iteration
-
- IterationInfo(int) - Constructor for class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
-
- IterationInfo(int, ClusterSetInfo) - Constructor for class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
-
- IterationListener - Interface in org.deeplearning4j.optimize.api
-
Each epoch the listener is called, mainly used for debugging or visualizations
- iterationListener - Variable in class org.deeplearning4j.plot.Tsne
-
- iterationListeners - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- iterationListeners - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- iterations(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- iterator() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- iterator() - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Returns an iterator over the elements in this applyTransformToDestination.
- IteratorIterator(Iterator, Factory<Iterator<T>>) - Constructor for class org.deeplearning4j.berkeley.Iterators.IteratorIterator
-
- Iterators - Class in org.deeplearning4j.berkeley
-
- Iterators.FilteredIterator<T> - Class in org.deeplearning4j.berkeley
-
Creates an iterator that only returns items of a base iterator that pass
a filter.
- Iterators.IteratorIterator<T> - Class in org.deeplearning4j.berkeley
-
Wraps a two-level iteration scenario in an iterator.
- Iterators.Transform<S,T> - Class in org.deeplearning4j.berkeley
-
WraTps a base iterator with a transformation function.
- Iterators.TransformingIterator<I,O> - Class in org.deeplearning4j.berkeley
-
- l1(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- l1 - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- l2(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- l2 - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- label() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- labelProbabilities(INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Returns the probabilities for each label
for each example row wise
- labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Returns the probabilities for each label
for each example row wise
- labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns the probabilities for each label
for each example row wise
- labels - Variable in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- labels - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- lambert(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- lastChild() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- Layer - Interface in org.deeplearning4j.nn.api
-
Interface for a layer of a neural network.
- Layer - Class in org.deeplearning4j.nn.conf.layers
-
A neural network layer.
- Layer(Layer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.Layer
-
- layer(Layer) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- layer - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- layer(int, Layer) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- Layer.Builder<T extends Layer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- Layer.Type - Enum in org.deeplearning4j.nn.api
-
- layerConf() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- layerConfig - Variable in class org.deeplearning4j.nn.layers.factory.DefaultLayerFactory
-
- LayerFactories - Class in org.deeplearning4j.nn.layers.factory
-
Static method for finding which layer factory to use
- LayerFactories() - Constructor for class org.deeplearning4j.nn.layers.factory.LayerFactories
-
- LayerFactory - Interface in org.deeplearning4j.nn.api
-
Common interface for creating neural network layers.
- layerIndex - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- LayerOverride - Class in org.deeplearning4j.nn.conf.override
-
Layer override
- LayerOverride(int, Layer) - Constructor for class org.deeplearning4j.nn.conf.override.LayerOverride
-
- layers - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- layerWiseConfigurations - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- LBFGS - Class in org.deeplearning4j.optimize.solvers
-
LBFGS
- LBFGS(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.LBFGS
-
- LBFGS(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.LBFGS
-
- learningRate(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- learningRate(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- learningRate - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- learningRate(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- learningRate - Variable in class org.deeplearning4j.plot.Tsne
-
- leftChild(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- LESS - Static variable in class org.deeplearning4j.clustering.kdtree.KDTree
-
- LexicographicPairComparator(Comparator<F>, Comparator<S>) - Constructor for class org.deeplearning4j.berkeley.Pair.LexicographicPairComparator
-
- LFW - Static variable in class org.deeplearning4j.base.LFWLoader
-
- lfw() - Static method in class org.deeplearning4j.datasets.DataSets
-
- lfw(int) - Static method in class org.deeplearning4j.datasets.DataSets
-
- LFW_URL - Static variable in class org.deeplearning4j.base.LFWLoader
-
- LFWDataFetcher - Class in org.deeplearning4j.datasets.fetchers
-
Data fetcher for the LFW faces dataset
- LFWDataFetcher(int, int) - Constructor for class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
-
- LFWDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
-
- LFWDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
- LFWDataSetIterator(int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
- LFWDataSetIterator(int, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
- LFWDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
- LFWDataSetIterator(int, int, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
- LFWLoader - Class in org.deeplearning4j.base
-
Loads LFW faces data transform.
- LFWLoader() - Constructor for class org.deeplearning4j.base.LFWLoader
-
- LFWLoader(int, int) - Constructor for class org.deeplearning4j.base.LFWLoader
-
- limitDecimalTo2(double) - Static method in class org.deeplearning4j.util.StringUtils
-
- LineGradientDescent - Class in org.deeplearning4j.optimize.solvers
-
Stochastic Gradient Descent with Line Search
- LineGradientDescent(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.LineGradientDescent
-
- LineGradientDescent(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.LineGradientDescent
-
- lineMaximizer - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- LineOptimizer - Interface in org.deeplearning4j.optimize.api
-
Line optimizer interface adapted from mallet
- lineSearch(double, INDArray, INDArray) - Method in class org.deeplearning4j.optimize.solvers.StochasticHessianFree
-
Search with the proposed objective
- list(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- ListBuilder(Map<Integer, NeuralNetConfiguration.Builder>) - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- ListDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
Wraps a data applyTransformToDestination collection
- ListDataSetIterator(Collection<DataSet>, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- ListDataSetIterator(Collection<DataSet>) - Constructor for class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
Initializes with a batch of 5
- listener(IterationListener...) - Method in class org.deeplearning4j.optimize.Solver.Builder
-
- listeners(Collection<IterationListener>) - Method in class org.deeplearning4j.optimize.Solver.Builder
-
- LoadAndDraw - Class in org.deeplearning4j.datasets.mnist.draw
-
- LoadAndDraw() - Constructor for class org.deeplearning4j.datasets.mnist.draw.LoadAndDraw
-
- loadIris(int, int) - Static method in class org.deeplearning4j.base.IrisUtils
-
- LOCAL_DIR_NAME - Static variable in class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher
-
- log - Static variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- log - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- log - Static variable in class org.deeplearning4j.plot.Tsne
-
- log2 - Static variable in class org.deeplearning4j.util.MathUtils
-
The natural logarithm of 2.
- log2(double) - Static method in class org.deeplearning4j.util.MathUtils
-
Returns the logarithm of a for base 2.
- logAdd(float, float) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Returns the log of the sum of two numbers, which are themselves input in
log form.
- logAdd(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Returns the log of the sum of two numbers, which are themselves input in
log form.
- logAdd(float[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- logAdd(double[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- logAdd(List<Double>) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- logAdd(float[], int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- logAdd(double[], int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- logAdd(Counter<T>) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- logAdd_Old(float[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- logNormalize(double[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- logs2probs(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Converts an array containing the natural logarithms of
probabilities stored in a vector back into probabilities.
- logSubtract(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- LOGTOLERANCE - Static variable in class org.deeplearning4j.berkeley.SloppyMath
-
If a difference is bigger than this in log terms, then the sum or
difference of them will just be the larger (to 12 or so decimal places
for double, and 7 or 8 for float).
- longestCommonSubstring(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Computes the longest common substring of s and t.
- lookingAt(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Say whether this regular expression can be found at the beginning of
this String.
- lossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- lossFunction(LossFunctions.LossFunction) - Method in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- lossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer
-
- lossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- lossFunction(LossFunctions.LossFunction) - Method in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- lossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
-
- LossPlotterIterationListener - Class in org.deeplearning4j.plot.iterationlistener
-
Reference: https://cs231n.github.io/neural-networks-3/
- LossPlotterIterationListener(int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.LossPlotterIterationListener
-
- LossPlotterIterationListener(int, NeuralNetPlotter) - Constructor for class org.deeplearning4j.plot.iterationlistener.LossPlotterIterationListener
-
- LossPlotterIterationListener(int, NeuralNetPlotter, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.LossPlotterIterationListener
-
- LossPlotterIterationListener(int) - Constructor for class org.deeplearning4j.plot.iterationlistener.LossPlotterIterationListener
-
- main(String[]) - Static method in class org.deeplearning4j.berkeley.Counter
-
- main(String[]) - Static method in class org.deeplearning4j.berkeley.CounterMap
-
- main(String[]) - Static method in class org.deeplearning4j.berkeley.PriorityQueue
-
- main(String[]) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Tests the hypergeometric distribution code, or other cooccurrences provided
in this module.
- main(String[]) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- main(String[]) - Static method in class org.deeplearning4j.datasets.creator.MnistDataSetCreator
-
- main(String[]) - Static method in class org.deeplearning4j.datasets.mnist.draw.LoadAndDraw
-
- main(String[]) - Static method in class org.deeplearning4j.eval.ConfusionMatrix
-
- makePair(S, T) - Static method in class org.deeplearning4j.berkeley.Pair
-
- makeTriple(S, T, U) - Static method in class org.deeplearning4j.berkeley.Triple
-
- manhattanDistance(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This will calculate the Manhattan distance between two sets of points.
- mapByPrimaryKey(int) - Method in class org.deeplearning4j.util.StringGrid
-
- MapFactory<K,V> - Class in org.deeplearning4j.berkeley
-
The MapFactory is a mechanism for specifying what kind of map is to be used
by some object.
- MapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory
-
- MapFactory.HashMapFactory<K,V> - Class in org.deeplearning4j.berkeley
-
- MapFactory.IdentityHashMapFactory<K,V> - Class in org.deeplearning4j.berkeley
-
- MapFactory.TreeMapFactory<K,V> - Class in org.deeplearning4j.berkeley
-
- MapFactory.WeakHashMapFactory<K,V> - Class in org.deeplearning4j.berkeley
-
- mapper() - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Object mapper for serialization of configurations
- mapperYaml() - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Object mapper for serialization of configurations
- mask - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- MASTER_PATH - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
-
- MASTER_URL - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
-
- matches(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Say whether this regular expression matches
this String.
- MathUtils - Class in org.deeplearning4j.util
-
This is a math utils class.
- MathUtils() - Constructor for class org.deeplearning4j.util.MathUtils
-
- max() - Method in class org.deeplearning4j.berkeley.Counter
-
- max(int, int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Returns the minimum of three int values.
- max(float, float) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Returns the greater of two float values.
- max(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Returns the greater of two double values.
- max(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
- maxIndex(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Returns index of maximum element in a given
array of doubles.
- maxIter - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- maxIter - Variable in class org.deeplearning4j.plot.Tsne
-
- maxLengthIterator(Iterator<T>, int) - Static method in class org.deeplearning4j.berkeley.Iterators
-
Provides a max number of elements for an underlying base iterator.
- maxNumLineSearchIterations(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- maxNumLineSearchIterations - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- mean(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Computes the mean for an array of doubles.
- merge(Layer, int) - Method in interface org.deeplearning4j.nn.api.Layer
-
Parameter averaging
- merge(Layer, int) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
Averages the given logistic regression from a mini batch into this layer
- merge(Layer, int) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- merge(Layer, int) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- merge(Layer, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Averages the given logistic regression
from a mini batch in to this one
- merge(MultiLayerNetwork, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Merges this network with the other one.
- merge(int, int) - Method in class org.deeplearning4j.util.StringGrid
-
- mergeCoords(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This will merge the coordinates of the given coordinate system.
- mergeCoords(List<Double>, List<Double>) - Static method in class org.deeplearning4j.util.MathUtils
-
This will merge the coordinates of the given coordinate system.
- min() - Method in class org.deeplearning4j.berkeley.Counter
-
- min(int, int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Returns the minimum of three int values.
- min(float, float) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Returns the smaller of two float values.
- min(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Returns the smaller of two double values.
- min(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
- minDistance(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- minGain(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- minGain - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- minGain(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- minGain - Variable in class org.deeplearning4j.plot.Tsne
-
- miniBatch(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- miniBatch - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- minimize(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- minimize - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- mnist() - Static method in class org.deeplearning4j.datasets.DataSets
-
- mnist(int) - Static method in class org.deeplearning4j.datasets.DataSets
-
- MnistDataFetcher - Class in org.deeplearning4j.datasets.fetchers
-
Data fetcher for the MNIST dataset
- MnistDataFetcher(boolean) - Constructor for class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
Constructor telling whether to binarize the dataset or not
- MnistDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- MnistDataSetCreator - Class in org.deeplearning4j.datasets.creator
-
- MnistDataSetCreator() - Constructor for class org.deeplearning4j.datasets.creator.MnistDataSetCreator
-
- MnistDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
Mnist data applyTransformToDestination iterator.
- MnistDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator
-
- MnistDataSetIterator(int, int, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator
-
Whether to binarize the data or not
- MnistDbFile - Class in org.deeplearning4j.datasets.mnist
-
MNIST database file containing entries that can represent image or label
data.
- MnistDbFile(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Creates new instance and reads the header information.
- MnistFetcher - Class in org.deeplearning4j.base
-
- MnistFetcher() - Constructor for class org.deeplearning4j.base.MnistFetcher
-
- MnistImageFile - Class in org.deeplearning4j.datasets.mnist
-
MNIST database image file.
- MnistImageFile(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Creates new MNIST database image file ready for reading.
- MnistLabelFile - Class in org.deeplearning4j.datasets.mnist
-
MNIST database label file.
- MnistLabelFile(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistLabelFile
-
Creates new MNIST database label file ready for reading.
- MnistManager - Class in org.deeplearning4j.datasets.mnist
-
Utility class for working with the MNIST database.
- MnistManager(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistManager
-
Constructs an instance managing the two given data files.
- Model - Interface in org.deeplearning4j.nn.api
-
A Model is meant for predicting something from data.
- model(Model) - Method in class org.deeplearning4j.optimize.Solver.Builder
-
- model - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- momentum(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- momentum - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- momentum - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- momentum - Variable in class org.deeplearning4j.plot.Tsne
-
- momentumAfter(Map<Integer, Double>) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- momentumAfter - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- mostLikelyInSequence(INDArray) - Method in interface org.deeplearning4j.nn.api.SequenceClassifier
-
- movingAverage(INDArray, int) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Calculate a moving average given the length
- MovingWindowBaseDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
DataSetIterator for moving window (rotating matrices)
- MovingWindowBaseDataSetIterator(int, int, DataSet, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.MovingWindowBaseDataSetIterator
-
- MovingWindowDataSetFetcher - Class in org.deeplearning4j.datasets.iterator.impl
-
Moving window data fetcher.
- MovingWindowDataSetFetcher(DataSet, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MovingWindowDataSetFetcher
-
- MovingWindowMatrix - Class in org.deeplearning4j.util
-
Moving window on a matrix (usually used for images)
Given a: This is a list of flattened arrays:
1 1 1 1 1 1 2 2
2 2 2 2 ----> 1 1 2 2
3 3 3 3 3 3 4 4
4 4 4 4 3 3 4 4
- MovingWindowMatrix(INDArray, int, int, boolean) - Constructor for class org.deeplearning4j.util.MovingWindowMatrix
-
- MovingWindowMatrix(INDArray, int, int) - Constructor for class org.deeplearning4j.util.MovingWindowMatrix
-
Same as calling new MovingWindowMatrix(toSlice,windowRowSize,windowColumnSize,false)
- MULTI_LAYER_CONF - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
-
- MultiDimensionalMap<K,T,V> - Class in org.deeplearning4j.util
-
Multiple key map
- MultiDimensionalMap(Map<Pair<K, T>, V>) - Constructor for class org.deeplearning4j.util.MultiDimensionalMap
-
- MultiDimensionalMap.Entry<K,T,V> - Class in org.deeplearning4j.util
-
- MultiDimensionalSet<K,V> - Class in org.deeplearning4j.util
-
Created by agibsonccc on 4/29/14.
- MultiDimensionalSet(Set<Pair<K, V>>) - Constructor for class org.deeplearning4j.util.MultiDimensionalSet
-
- MultiLayerConfiguration - Class in org.deeplearning4j.nn.conf
-
Configuration for a multi layer network
- MultiLayerConfiguration() - Constructor for class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- MultiLayerConfiguration.Builder - Class in org.deeplearning4j.nn.conf
-
- MultiLayerNetwork - Class in org.deeplearning4j.nn.multilayer
-
A base class for a multi
layer neural network with a logistic output layer
and multiple hidden neuralNets.
- MultiLayerNetwork(MultiLayerConfiguration) - Constructor for class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- MultiLayerNetwork(String, INDArray) - Constructor for class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Initialize the network based on the configuration
- MultiLayerNetwork(MultiLayerConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Initialize the network based on the configuraiton
- MultiLayerNetworkReconstructionRender - Class in org.deeplearning4j.plot
-
Reconstruction renders for a multi layer network
- MultiLayerNetworkReconstructionRender(DataSetIterator, MultiLayerNetwork, int) - Constructor for class org.deeplearning4j.plot.MultiLayerNetworkReconstructionRender
-
- MultiLayerNetworkReconstructionRender(DataSetIterator, MultiLayerNetwork) - Constructor for class org.deeplearning4j.plot.MultiLayerNetworkReconstructionRender
-
- MultiLayerUpdater - Class in org.deeplearning4j.nn.updater
-
MultiLayerUpdater: Gradient updater for MultiLayerNetworks.
- MultiLayerUpdater(MultiLayerNetwork) - Constructor for class org.deeplearning4j.nn.updater.MultiLayerUpdater
-
- MultiLayerUtil - Class in org.deeplearning4j.util
-
Various cooccurrences for manipulating a multi layer network
- MultiLayerUtil() - Constructor for class org.deeplearning4j.util.MultiLayerUtil
-
- MultipleEpochsIterator - Class in org.deeplearning4j.datasets.iterator
-
A dataset iterator for doing multiple passes over a dataset
- MultipleEpochsIterator(int, DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
- MultiThreadUtils - Class in org.deeplearning4j.util
-
- MultiThreadUtils() - Constructor for class org.deeplearning4j.util.MultiThreadUtils
-
- MyMethod<I,O> - Interface in org.deeplearning4j.berkeley
-
A function wrapping interface.
- NAME_SPACE - Static variable in interface org.deeplearning4j.datasets.creator.DataSetIteratorFactory
-
- nChooseK(int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Computes n choose k in an efficient way.
- nearestCluster(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- nearestCluster(INDArray) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- negative() - Method in class org.deeplearning4j.eval.Evaluation
-
Total negatives true negatives + false positives
- NegativeDefaultStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions
-
Inverse step function
- NegativeDefaultStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.NegativeDefaultStepFunction
-
- NegativeDefaultStepFunction - Class in org.deeplearning4j.optimize.stepfunctions
-
Inverse step function
- NegativeDefaultStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
-
- NegativeGradientStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions
-
Subtract the line
- NegativeGradientStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.NegativeGradientStepFunction
-
- NegativeGradientStepFunction - Class in org.deeplearning4j.optimize.stepfunctions
-
Subtract the line
- NegativeGradientStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
-
- NesterovsUpdater - Class in org.deeplearning4j.nn.updater
-
- NesterovsUpdater() - Constructor for class org.deeplearning4j.nn.updater.NesterovsUpdater
-
- NEURAL_NET_CONF - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
-
- NeuralNetConfiguration - Class in org.deeplearning4j.nn.conf
-
A Serializable configuration
for neural nets that covers per layer parameters
- NeuralNetConfiguration() - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- NeuralNetConfiguration.Builder - Class in org.deeplearning4j.nn.conf
-
- NeuralNetConfiguration.ListBuilder - Class in org.deeplearning4j.nn.conf
-
Fluent interface for building a list of configurations
- NeuralNetPlotter - Class in org.deeplearning4j.plot
-
Credit to :
http://yosinski.com/media/papers/Yosinski2012VisuallyDebuggingRestrictedBoltzmannMachine.pdf
for visualizations
- NeuralNetPlotter() - Constructor for class org.deeplearning4j.plot.NeuralNetPlotter
-
- NeuralNetPlotterIterationListener - Class in org.deeplearning4j.plot.iterationlistener
-
Renders network activations every n iterations
- NeuralNetPlotterIterationListener(int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
-
- NeuralNetPlotterIterationListener(int, int) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
-
- NeuralNetPlotterIterationListener(int, int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
-
- NeuralNetPlotterIterationListener(int, NeuralNetPlotter, int) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
-
- NeuralNetPlotterIterationListener(int, NeuralNetPlotter, int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
-
- NeuralNetPlotterIterationListener(int) - Constructor for class org.deeplearning4j.plot.iterationlistener.NeuralNetPlotterIterationListener
-
- NeuralNetworkReconstructionRender - Class in org.deeplearning4j.plot
-
Neural Network reconstruction renderer
- NeuralNetworkReconstructionRender(DataSetIterator, Layer) - Constructor for class org.deeplearning4j.plot.NeuralNetworkReconstructionRender
-
- newExecutorService() - Static method in class org.deeplearning4j.util.MultiThreadUtils
-
- newHashBackedMap() - Static method in class org.deeplearning4j.util.MultiDimensionalMap
-
Thread safe hash map impl
- newInstance(Object...) - Method in class org.deeplearning4j.berkeley.Factory.DefaultFactory
-
- newInstance(Object...) - Method in interface org.deeplearning4j.berkeley.Factory
-
- newInstance(Class<T>, Configuration) - Static method in class org.deeplearning4j.util.ReflectionUtils
-
Create an object for the given class and initialize it from conf
- newIterable(Iterator<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
-
Wraps an iterator as an iterable
- newPair(S, T) - Static method in class org.deeplearning4j.berkeley.Pair
-
- newThreadSafeHashBackedMap() - Static method in class org.deeplearning4j.util.MultiDimensionalMap
-
Thread safe hash map implementation
- newThreadSafeTreeBackedMap() - Static method in class org.deeplearning4j.util.MultiDimensionalMap
-
Thread safe sorted map implementation
- newTreeBackedMap() - Static method in class org.deeplearning4j.util.MultiDimensionalMap
-
Tree map implementation
- next() - Method in class org.deeplearning4j.berkeley.Iterators.FilteredIterator
-
- next() - Method in class org.deeplearning4j.berkeley.Iterators.IteratorIterator
-
- next() - Method in class org.deeplearning4j.berkeley.Iterators.Transform
-
- next() - Method in class org.deeplearning4j.berkeley.Iterators.TransformingIterator
-
- next() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- next() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface
-
Returns the element in the queue with highest priority, and pops it from
the queue.
- next(int) - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- next() - Method in class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
-
- next() - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- next() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- next() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
Returns the next data applyTransformToDestination
- next() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Like the standard next method but allows a
customizable number of examples returned
- next() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Returns the next element in the iteration.
- next(int) - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Like the standard next method but allows a
customizable number of examples returned
- next() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Returns the next element in the iteration.
- next() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Move to the next entry.
- next() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- nextImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Move the cursor to the next image.
- nextList(List<Iterator<T>>) - Static method in class org.deeplearning4j.berkeley.Iterators
-
- nextPowOf2(long) - Static method in class org.deeplearning4j.util.MathUtils
-
See: http://stackoverflow.com/questions/466204/rounding-off-to-nearest-power-of-2
- nIn - Variable in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
-
- nIn(int) - Method in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
-
- nIn - Variable in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- nn(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.KDTree
-
Query for nearest neighbor.
- Node(int, double) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- NODE_RATIO - Static variable in class org.deeplearning4j.clustering.sptree.SpTree
-
- noNaNDivide(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- NONE - Static variable in class org.deeplearning4j.util.StringGrid
-
- NoOpUpdater - Class in org.deeplearning4j.nn.updater
-
- NoOpUpdater() - Constructor for class org.deeplearning4j.nn.updater.NoOpUpdater
-
- Norm2Termination - Class in org.deeplearning4j.optimize.terminations
-
Terminate if the norm2 of the gradient is < a certain tolerance
- Norm2Termination(double) - Constructor for class org.deeplearning4j.optimize.terminations.Norm2Termination
-
- NormalDistribution - Class in org.deeplearning4j.nn.conf.distribution
-
A normal distribution.
- NormalDistribution(double, double) - Constructor for class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
Create a normal distribution
with the given mean and std
- normalize() - Method in class org.deeplearning4j.berkeley.Counter
-
Destructively normalize this Counter in place.
- normalize() - Method in class org.deeplearning4j.berkeley.CounterMap
-
- normalize() - Method in class org.deeplearning4j.datasets.vectorizer.ImageVectorizer
-
Normalize the input image by row sums
- normalize(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- normalize - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- normalize(boolean) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- normalize - Variable in class org.deeplearning4j.plot.Tsne
-
- normalize(double, double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
Normalize a value
(val - min) / (max - min)
- normalize(double[], double) - Static method in class org.deeplearning4j.util.MathUtils
-
Normalizes the doubles in the array using the given value.
- normalized(int[], int) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil
-
Normalized weight init
- normalizeToOne(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
- normalizeWithDiscount(double) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- nOut - Variable in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
-
- nOut(int) - Method in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
-
- nOut - Variable in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- nthIndex(String, char, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns the index of the nth occurrence of ch in s, or -1
if there are less than n occurrences of ch.
- NUM_EXAMPLES - Static variable in class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
-
- NUM_EXAMPLES - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- NUM_IMAGES - Static variable in class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
-
- NUM_PASSES - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
-
- numChannels(int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Returns the number of
feature maps for a given shape (must be at least 3 dimensions
- numExamples() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- numExamples - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Total number of examples in the dataset
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Total number of examples in the dataset
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- numFeatureMap(NeuralNetConfiguration) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- numIterations - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- numLabels() - Method in interface org.deeplearning4j.nn.api.Classifier
-
Returns the number of possible labels
- numLabels() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Returns the number of possible labels
- numLabels() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns the number of possible labels
- numOutcomes - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- numParams() - Method in interface org.deeplearning4j.nn.api.Model
-
the number of parameters for the model
- numParams() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
The number of parameters for the model
- numParams() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- numParams() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns a 1 x m vector where the vector is composed of
a flattened vector of all of the weights for the
various neuralNets and output layer
- numParams() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- pack() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Packs a set of matrices in to one vector,
where the matrices in this case are the w,hbias at each layer
and the output layer w,bias
- pack(List<Pair<INDArray, INDArray>>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Packs a set of matrices in to one vector
- pad(String, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Return a String of length a minimum of totalChars characters by
padding the input String str with spaces.
- pad(Object, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Pads the toString value of the given Object.
- padding(int...) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- padding - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- padding(int...) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- padding - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- padLeft(String, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Pads the given String to the left with spaces to ensure that it's
at least totalChars long.
- padLeft(Object, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- padLeft(int, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- padLeft(double, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- padOrTrim(String, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Pad or trim so as to produce a string of exactly a certain length.
- padOrTrim(Object, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Pad or trim the toString value of the given Object.
- paintComponent(Graphics) - Method in class org.deeplearning4j.plot.FilterPanel
-
- Pair<F,S> - Class in org.deeplearning4j.berkeley
-
A generic-typed pair of objects.
- Pair(F, S) - Constructor for class org.deeplearning4j.berkeley.Pair
-
- Pair.DefaultLexicographicPairComparator<F extends Comparable<F>,S extends Comparable<S>> - Class in org.deeplearning4j.berkeley
-
- Pair.FirstComparator<S extends Comparable<? super S>,T> - Class in org.deeplearning4j.berkeley
-
- Pair.LexicographicPairComparator<F,S> - Class in org.deeplearning4j.berkeley
-
- Pair.ReverseFirstComparator<S extends Comparable<? super S>,T> - Class in org.deeplearning4j.berkeley
-
- Pair.ReverseSecondComparator<S,T extends Comparable<? super T>> - Class in org.deeplearning4j.berkeley
-
- Pair.SecondComparator<S,T extends Comparable<? super T>> - Class in org.deeplearning4j.berkeley
-
- parallelCounterMap() - Static method in class org.deeplearning4j.berkeley.CounterMap
-
Returns a thread safe counter map
- parallelTasks(List<Runnable>, ExecutorService) - Static method in class org.deeplearning4j.util.MultiThreadUtils
-
- ParamInitializer - Interface in org.deeplearning4j.nn.api
-
Param initializer for a layer
- paramInitializer - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- params() - Method in interface org.deeplearning4j.nn.api.Model
-
Parameters of the model (if any)
- params - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- params() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
Returns the parameters of the neural network as a flattened row vector
- params() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- params() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns a 1 x m vector where the vector is composed of
a flattened vector of all of the weights for the
various neuralNets(w,hbias NOT VBIAS) and output layer
- params() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- PARAMS_KEY - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- paramTable() - Method in interface org.deeplearning4j.nn.api.Model
-
The param table
- paramTable() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- paramTable() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- paramTable() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- parent(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- parent(Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Returns the parent of the passed in tree via traversal
- parent() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- parse(String, Class<E>) - Static method in class org.deeplearning4j.util.EnumUtil
-
- parseCommandLineArguments(String[]) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
A simpler form of command line argument parsing.
- partitionVariable(List<Double>, int) - Static method in class org.deeplearning4j.util.MathUtils
-
This will partition the given whole variable data applyTransformToDestination in to the specified chunk number.
- peek() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- peek() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface
-
Returns the highest-priority element in the queue, but does not pop it.
- peek() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- pennPOSToWordnetPOS(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Computes the WordNet 2.0 POS tag corresponding to the PTB POS tag s.
- permutation(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the permutation of n choose r.
- perplexity(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- perplexity - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- perplexity(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- perplexity - Variable in class org.deeplearning4j.plot.Tsne
-
- plot(INDArray, int, List<String>, String) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Plot tsne
- plot() - Method in class org.deeplearning4j.plot.PlotFilters
-
Plot the image
- plot(INDArray, int, List<String>) - Method in class org.deeplearning4j.plot.Tsne
-
Plot tsne (write the coordinates file)
- plot(INDArray, int, List<String>, String) - Method in class org.deeplearning4j.plot.Tsne
-
Plot tsne
- plotActivations(Layer) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
plotActivations show how hidden neurons are used, how often on vs.
- PlotFilters - Class in org.deeplearning4j.plot
-
Based on the work by krizshevy et.
- PlotFilters(INDArray, int[], int[], int[]) - Constructor for class org.deeplearning4j.plot.PlotFilters
-
- PlotFiltersIterationListener - Class in org.deeplearning4j.plot.iterationlistener
-
- PlotFiltersIterationListener(PlotFilters, List<String>, int) - Constructor for class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- plotNetworkGradient(Layer, Gradient) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
plotNetworkGradient used for debugging RBM gradients with different data visualizations
- plotNetworkGradient(Layer, INDArray) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- plotWeightHistograms(Layer, Gradient) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
plotWeightHistograms graphs values of vBias, W, and hBias on aggregate and
most recent mini-batch updates (-gradient)
- plotWeightHistograms(Layer) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- Point - Class in org.deeplearning4j.clustering.cluster
-
- Point(INDArray) - Constructor for class org.deeplearning4j.clustering.cluster.Point
-
- Point(String, INDArray) - Constructor for class org.deeplearning4j.clustering.cluster.Point
-
- Point(String, String, double[]) - Constructor for class org.deeplearning4j.clustering.cluster.Point
-
- Point(String, String, INDArray) - Constructor for class org.deeplearning4j.clustering.cluster.Point
-
- point(INDArray) - Static method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- PointClassification - Class in org.deeplearning4j.clustering.cluster
-
- PointClassification(Cluster, double, boolean) - Constructor for class org.deeplearning4j.clustering.cluster.PointClassification
-
- poll() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- poolingType(SubsamplingLayer.PoolingType) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- poolingType - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- positive() - Method in class org.deeplearning4j.eval.Evaluation
-
Returns all of the positive guesses:
true positive + false negative
- postApply(Layer, INDArray, String) - Method in class org.deeplearning4j.nn.updater.BaseUpdater
-
Apply the regularization
- postFirstStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- postStep(INDArray) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
After the step has been made, do an action
- postStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
Post step to update searchDirection with new gradient and parameter information
- postStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.ConjugateGradient
-
- postStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.LBFGS
-
- postStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.LineGradientDescent
-
- postStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.StochasticGradientDescent
-
- precision(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the precision for a given label
- precision() - Method in class org.deeplearning4j.eval.Evaluation
-
Total precision based on guesses so far
- predict(INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Takes in a list of examples
For each row, returns a label
- predict(INDArray) - Method in interface org.deeplearning4j.nn.api.SequenceClassifier
-
- predict(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Returns the predictions for each example in the dataset
- predict(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- predict(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns the predictions for each example in the dataset
- prediction() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- preOutput(INDArray) - Method in interface org.deeplearning4j.nn.api.Layer
-
Raw activations
- preOutput(INDArray, boolean) - Method in interface org.deeplearning4j.nn.api.Layer
-
Raw activations
- preOutput(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- preOutput(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
Classify input
- preOutput(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- preOutput(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- preOutput(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- preOutput(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- preOutput(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- preOutput(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- preOutput(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- preOutput(INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- preOutput2d(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- preOutput2d(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- prependToEach(String, int) - Method in class org.deeplearning4j.util.StringGrid
-
- preProcess(INDArray, Layer) - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor
-
Pre preProcess input/activations for a multi layer network
- preProcess(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
-
- preProcess(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- preProcess(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- preProcess(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- preProcess(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- preProcess(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
-
- preProcess(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- preProcess(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.UnitVarianceProcessor
-
- preProcess(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanAndUnitVariancePreProcessor
-
- preProcess(INDArray, Layer) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanPrePreProcessor
-
- preProcessLine() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
Pre preProcess a line before an iteration
- preProcessLine() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
Pre preProcess to setup initial searchDirection approximation
- preProcessLine() - Method in class org.deeplearning4j.optimize.solvers.ConjugateGradient
-
- preProcessLine() - Method in class org.deeplearning4j.optimize.solvers.LBFGS
-
- preProcessLine() - Method in class org.deeplearning4j.optimize.solvers.LineGradientDescent
-
- preProcessLine() - Method in class org.deeplearning4j.optimize.solvers.StochasticGradientDescent
-
- preProcessor - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- pretrain - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- pretrain(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
Whether to do pre train or not
- pretrain - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- pretrain(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- pretrain(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
This unsupervised learning method runs
contrastive divergence on each RBM layer in the network.
- pretrain(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
This unsupervised learning method runs
contrastive divergence on each RBM layer in the network.
- PretrainLayerFactory - Class in org.deeplearning4j.nn.layers.factory
-
Used for creating pretrain neural net layers
- PretrainLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.PretrainLayerFactory
-
- PretrainParamInitializer - Class in org.deeplearning4j.nn.params
-
Pretrain weight initializer.
- PretrainParamInitializer() - Constructor for class org.deeplearning4j.nn.params.PretrainParamInitializer
-
- prev() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Move to the previous entry.
- prevImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Move the cursor to the previous image.
- printConfiguration() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Prints the configuration
- printDataFilePath() - Static method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- printGraphFilePath() - Static method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- printStringOneCharPerLine(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- printThreadInfo(PrintWriter, String) - Static method in class org.deeplearning4j.util.ReflectionUtils
-
Print all of the thread's information and stack traces.
- printToFile(File, String, boolean) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Prints to a file.
- printToFile(File, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Prints to a file.
- printToFile(String, String, boolean) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Prints to a file.
- printToFile(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Prints to a file.
- PriorityQueue<E> - Class in org.deeplearning4j.berkeley
-
A priority queue based on a binary heap.
- PriorityQueue() - Constructor for class org.deeplearning4j.berkeley.PriorityQueue
-
- PriorityQueue(int) - Constructor for class org.deeplearning4j.berkeley.PriorityQueue
-
- PriorityQueueInterface<E> - Interface in org.deeplearning4j.berkeley
-
- probRound(double, Random) - Static method in class org.deeplearning4j.util.MathUtils
-
Rounds a double to the next nearest integer value in a probabilistic
fashion (e.g.
- probToLogOdds(double) - Static method in class org.deeplearning4j.util.MathUtils
-
Returns the log-odds for a given probability.
- propDown(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
Calculates the activation of the hidden:
activation(h * W + vbias)
- propUp(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
Calculates the activation of the visible :
sigmoid(v * W + hbias)
- pruneKeysBelowThreshold(double) - Method in class org.deeplearning4j.berkeley.Counter
-
- put(E, double, boolean) - Method in class org.deeplearning4j.berkeley.Counter
-
Set the count for the given key if it is larger than the previous one;
- put(E, double) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- put(E, double) - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface
-
Adds a key to the queue with the given priority.
- put(Pair<K, T>, V) - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
Associates the specified value with the specified key in this map
(optional operation).
- put(K, T, V) - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
- putAll(Map<? extends Pair<K, T>, ? extends V>) - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
Copies all of the mappings from the specified map to this map
(optional operation).
- r - Static variable in class org.deeplearning4j.plot.Tsne
-
- Random - Class in org.deeplearning4j.nn.conf.rng
-
Deprecated.
- Random() - Constructor for class org.deeplearning4j.nn.conf.rng.Random
-
Deprecated.
- randomDoubleBetween(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
- randomFloatBetween(float, float) - Static method in class org.deeplearning4j.util.MathUtils
-
- randomNumberBetween(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
Generates a random integer between the specified numbers
- randomNumberBetween(double, double, RandomGenerator) - Static method in class org.deeplearning4j.util.MathUtils
-
Generates a random integer between the specified numbers
- Randoms - Class in org.deeplearning4j.nn.conf.rng
-
Deprecated.
- Randoms() - Constructor for class org.deeplearning4j.nn.conf.rng.Randoms
-
Deprecated.
- RawMnistDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
Mnist data with scaled pixels
- RawMnistDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.RawMnistDataSetIterator
-
- RBM - Class in org.deeplearning4j.nn.conf.layers
-
Restricted Boltzmann Machine.
- RBM - Class in org.deeplearning4j.nn.layers.feedforward.rbm
-
Restricted Boltzmann Machine.
- RBM(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
- RBM(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
- RBM.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- RBM.HiddenUnit - Enum in org.deeplearning4j.nn.conf.layers
-
- RBM.VisibleUnit - Enum in org.deeplearning4j.nn.conf.layers
-
- RBMUtil - Class in org.deeplearning4j.util
-
Handles various cooccurrences for RBM specific cooccurrences
- readImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Reads the image at the current position.
- readImage() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
Reads the current image.
- readjustToData() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
-
- readLabel() - Method in class org.deeplearning4j.datasets.mnist.MnistLabelFile
-
Reads the integer at the current position.
- readLabel() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
Reads the current label.
- readObject(File) - Static method in class org.deeplearning4j.util.SerializationUtils
-
- readObject(InputStream) - Static method in class org.deeplearning4j.util.SerializationUtils
-
Reads an object from the given input stream
- readString(DataInputStream, int) - Static method in class org.deeplearning4j.util.ByteUtil
-
- realMin - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- realMin - Variable in class org.deeplearning4j.plot.Tsne
-
- recall(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
Get the recall for a particular class label
- recall() - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the recall for the outcomes
- reconstruct(INDArray, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Reconstructs the input.
- ReconstructionDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
Wraps a data applyTransformToDestination iterator setting the first (feature matrix) as
the labels.
- ReconstructionDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
- RecordReaderDataSetIterator - Class in org.deeplearning4j.datasets.canova
-
Record reader dataset iterator
- RecordReaderDataSetIterator(RecordReader, int) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
Use the record reader and batch size; no labels
- RecordReaderDataSetIterator(RecordReader, int, int, int) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
Main constructor
- RecordReaderDataSetIterator(RecordReader) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- RecordReaderDataSetIterator(RecordReader, int, int) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- RecordReaderDataSetIterator(RecordReader, WritableConverter, int, int, int, boolean) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- RecordReaderDataSetIterator(RecordReader, WritableConverter, int, int, int) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- RecordReaderDataSetIterator(RecordReader, WritableConverter) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- RecordReaderDataSetIterator(RecordReader, WritableConverter, int, int) - Constructor for class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- RECURRENT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
Weights for previous time step -> current time step connections
- RECURRENT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.GRUParamInitializer
-
Weights for previous time step -> current time step connections
- RECURRENT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.ImageLSTMParamInitializer
-
- RecursiveAutoEncoder - Class in org.deeplearning4j.nn.conf.layers
-
Recursive AutoEncoder.
- RecursiveAutoEncoder - Class in org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive
-
Recursive AutoEncoder.
- RecursiveAutoEncoder(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- RecursiveAutoEncoder.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- RecursiveAutoEncoderLayerFactory - Class in org.deeplearning4j.nn.layers.factory
-
Recursive parameter initializer
- RecursiveAutoEncoderLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.RecursiveAutoEncoderLayerFactory
-
- RecursiveParamInitializer - Class in org.deeplearning4j.nn.params
-
Recursive autoencoder initializer
- RecursiveParamInitializer() - Constructor for class org.deeplearning4j.nn.params.RecursiveParamInitializer
-
- reDistributeParams() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Redistribute parameters handles
having parameters as a view
- reductionRatio(INDArray, double, double, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- ReflectionUtils - Class in org.deeplearning4j.util
-
General reflection utils
- ReflectionUtils() - Constructor for class org.deeplearning4j.util.ReflectionUtils
-
- refreshClusterCenter(Cluster, ClusterInfo) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- refreshClustersCenters(ClusterSet, ClusterSetInfo, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- regularization(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- relativeDifferance(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- remove() - Method in class org.deeplearning4j.berkeley.Iterators.FilteredIterator
-
- remove() - Method in class org.deeplearning4j.berkeley.Iterators.IteratorIterator
-
- remove() - Method in class org.deeplearning4j.berkeley.Iterators.Transform
-
- remove() - Method in class org.deeplearning4j.berkeley.Iterators.TransformingIterator
-
- remove() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- remove() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface
-
Not supported -- next() already removes the head of the queue.
- remove() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- remove(Object) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- remove() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- remove(Object) - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
Removes the mapping for a key from this map if it is present
(optional operation).
- remove(Object) - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Removes the specified element from this applyTransformToDestination if it is present
(optional operation).
- removeAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- removeAll(Collection<?>) - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Removes from this applyTransformToDestination all of its elements that are contained in the
specified collection (optional operation).
- removeClusterInfos(List<Cluster>) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- removeColumns(Integer...) - Method in class org.deeplearning4j.util.StringGrid
-
Removes the specified columns from the grid
- removeEmptyClusters(ClusterSetInfo) - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- removeEmptyClusters() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- removeFirst() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- removeKey(E) - Method in class org.deeplearning4j.berkeley.Counter
-
- removeKey(K) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- removeKeyFromEntries(E) - Method in class org.deeplearning4j.berkeley.Counter
-
- removePoint(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- removePoints() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- removePoints() - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- removePoints() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- removePoints() - Method in class org.deeplearning4j.clustering.Cluster
-
- removePoints() - Method in class org.deeplearning4j.clustering.ClusterSet
-
- removeRowsWithEmptyColumn(int) - Method in class org.deeplearning4j.util.StringGrid
-
Removes all rows with a column of NONE
- removeRowsWithEmptyColumn(int, String) - Method in class org.deeplearning4j.util.StringGrid
-
Removes all rows with a column of missingValue
- renderActivations(int, int, INDArray, String, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- renderFilter(Layer, int) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
renderFilter plot learned filter for each hidden neuron
- RenderFilterIterationListener - Class in org.deeplearning4j.plot.iterationlistener
-
- RenderFilterIterationListener(int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.RenderFilterIterationListener
-
- RenderFilterIterationListener(int, int) - Constructor for class org.deeplearning4j.plot.iterationlistener.RenderFilterIterationListener
-
- RenderFilterIterationListener(int, int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.RenderFilterIterationListener
-
- RenderFilterIterationListener(int, NeuralNetPlotter, int, boolean) - Constructor for class org.deeplearning4j.plot.iterationlistener.RenderFilterIterationListener
-
- RenderFilterIterationListener(int) - Constructor for class org.deeplearning4j.plot.iterationlistener.RenderFilterIterationListener
-
- renderFilters(INDArray, String, int, int, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
Once the probability image and weight histograms are
behaving satisfactorily, we plot the learned filter
for each hidden neuron, one per column of W.
- renderGraph(String, String, String) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
Calls out to python for rendering charts
- renderGraph(String, String, String, int, int) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
Calls out to python for rendering charts
- renderHiddenBiases(int, int, INDArray, String) - Method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- renderHistogram(INDArray, String, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
Groups values into 1 of 10 bins, sums, and renders
NOTE: this is "render histogram BS code";
- I'm not exactly concerned with how pretty it is.
- reset() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- reset() - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- reset() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
Returns the fetcher back to the beginning of the dataset
- reset() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Resets the iterator back to the beginning
- reset() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Resets the iterator back to the beginning
- reset() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- ReshapePreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
Reshape post processor.
Used to reshape activations on forward pass.
Also (optionally, if fromShape != null) used to reshape, weights*deltas
during backward pass.
- ReshapePreProcessor(int[], int[], boolean) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
-
- ReshapePreProcessor(int...) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
-
- ReshapePreProcessor(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
-
- retainAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- retainAll(Collection<?>) - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Retains only the elements in this applyTransformToDestination that are contained in the
specified collection (optional operation).
- reverse() - Method in class org.deeplearning4j.berkeley.Pair
-
- ReverseFirstComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.ReverseFirstComparator
-
- ReverseSecondComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.ReverseSecondComparator
-
- rho(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Ada delta coefficient
- rho - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- rightChild(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- rmsDecay(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- rmsDecay - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- RmsPropUpdater - Class in org.deeplearning4j.nn.updater
-
- RmsPropUpdater() - Constructor for class org.deeplearning4j.nn.updater.RmsPropUpdater
-
- rnnClearPreviousState() - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
Reset/clear the stateMap for rnnTimeStep()
- rnnClearPreviousState() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Clear the previous state of the RNN layers (if any).
- rnnGetPreviousState() - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
Returns a shallow copy of the stateMap
- rnnGetPreviousState(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Get the state of the RNN layer, as used in rnnTimeStep().
- RnnOutputLayer - Class in org.deeplearning4j.nn.conf.layers
-
- RnnOutputLayer - Class in org.deeplearning4j.nn.layers.recurrent
-
Recurrent Neural Network Output Layer.
Handles calculation of gradients etc for various objective functions.
Functionally the same as OutputLayer, but handles output and label reshaping
automatically.
Input and output activations are same as other RNN layers: 3 dimensions with shape
[miniBatchSize,nIn,timeSeriesLength] and [miniBatchSize,nOut,timeSeriesLength] respectively.
- RnnOutputLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- RnnOutputLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- RnnOutputLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- rnnSetPreviousState(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
Set the state map.
- rnnSetPreviousState(int, Map<String, INDArray>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Set the state of the RNN layer.
- rnnTimeStep(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
Do one or more time steps using the previous time step state stored in stateMap.
Can be used to efficiently do forward pass one or n-steps at a time (instead of doing
forward pass always from t=0)
If stateMap is empty, default initialization (usually zeros) is used
Implementations also update stateMap at the end of this method
- rnnTimeStep(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- rnnTimeStep(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- rnnTimeStep(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
If this MultiLayerNetwork contains one or more RNN layers: conduct forward pass (prediction)
but using previous stored state for any RNN layers.
- RnnToFeedForwardPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow RNN and feed-forward network layers to be used together.
For example, GravesLSTM -> OutputLayer or GravesLSTM -> DenseLayer
This does two things:
(a) Reshapes activations out of RNN layer (which is 3D with shape
[miniBatchSize,layerSize,timeSeriesLength]) into 2d activations (with shape
[miniBatchSize*timeSeriesLength,layerSize]) suitable for use in feed-forward layers.
(b) Reshapes 2d epsilons (weights*deltas from feed forward layer, with shape
[miniBatchSize*timeSeriesLength,layerSize]) into 3d epsilons (with shape
[miniBatchSize,layerSize,timeSeriesLength]) for use in RNN layer
- RnnToFeedForwardPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- rootMeansSquaredError(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the root mean squared error of two data sets
- round(double, int, int) - Static method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- round(double) - Static method in class org.deeplearning4j.util.MathUtils
-
Rounds a double to the next nearest integer value.
- roundDouble(double, int) - Static method in class org.deeplearning4j.util.MathUtils
-
Rounds a double to the given number of decimal places.
- roundFloat(float, int) - Static method in class org.deeplearning4j.util.MathUtils
-
Rounds a double to the given number of decimal places.
- runPairWise(List<V>, CounterMap.CountFunction<V>) - Static method in class org.deeplearning4j.berkeley.CounterMap
-
Build a counter map by iterating pairwise over the list.
- sample(Random) - Method in class org.deeplearning4j.berkeley.Counter
-
Will return a sample from the counter, will throw exception if any of the
counts are < 0.0 or if the totalCount() <= 0.0
- sample() - Method in class org.deeplearning4j.berkeley.Counter
-
Will return a sample from the counter, will throw exception if any of the
counts are < 0.0 or if the totalCount() <= 0.0
- sampleDoublesInInterval(double[][], int) - Static method in class org.deeplearning4j.util.MathUtils
-
- sampleHiddenGivenVisible(INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
Sample the hidden distribution given the visible
- sampleHiddenGivenVisible(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- sampleHiddenGivenVisible(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
Binomial sampling of the hidden values given visible
- sampleVisibleGivenHidden(INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
Sample the visible distribution given the hidden
- sampleVisibleGivenHidden(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- sampleVisibleGivenHidden(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
Guess the visible values given the hidden
- SamplingDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
A wrapper for a dataset to sample from.
- SamplingDataSetIterator(DataSet, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- saveImageToDisk(BufferedImage, String) - Static method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- saveObject(Object, File) - Static method in class org.deeplearning4j.util.SerializationUtils
-
- saveToDisk(String) - Method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- scale(double) - Method in class org.deeplearning4j.berkeley.Counter
-
- scale(double) - Method in class org.deeplearning4j.berkeley.CounterMap
-
Scale all entries in CounterMap
by scaleFactor
- scale(INDArray) - Method in class org.deeplearning4j.plot.PlotFilters
-
scale the data to between 0 and 1
- scaledClone(double) - Method in class org.deeplearning4j.berkeley.Counter
-
- score() - Method in interface org.deeplearning4j.nn.api.Model
-
The score for the model
- score - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- score() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
Objective function: the specified objective
- score() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- score() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- score - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- score(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Sets the input and labels and returns a score for the prediction
wrt true labels
- score() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Score of the model (relative to the objective function)
- score(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Score of the model (relative to the objective function)
- score() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
The score for the optimizer so far
- score - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- score() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- score() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- SCORE_KEY - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- ScoreIterationListener - Class in org.deeplearning4j.optimize.listeners
-
Score iteration listener
- ScoreIterationListener(int) - Constructor for class org.deeplearning4j.optimize.listeners.ScoreIterationListener
-
- ScoreIterationListener() - Constructor for class org.deeplearning4j.optimize.listeners.ScoreIterationListener
-
- search(DataPoint, int, List<DataPoint>, List<Double>) - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
- search(VPTree.Node, DataPoint, int, PriorityQueue<HeapItem>) - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
- SEARCH_DIR - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- searchState - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- SecondComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.SecondComparator
-
- seed(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- seed(long) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- seed - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- select(int, String) - Method in class org.deeplearning4j.util.StringGrid
-
- SequenceClassifier - Interface in org.deeplearning4j.nn.api
-
Created by agibsonccc on 8/27/14.
- SerializationUtils - Class in org.deeplearning4j.util
-
Serialization utils for saving and reading serializable objects
- SerializationUtils() - Constructor for class org.deeplearning4j.util.SerializationUtils
-
- setAbsTolx(double) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
Sets the tolerance of absolute diff in function value.
- setAccumulation(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- setAllCounts(double) - Method in class org.deeplearning4j.berkeley.Counter
-
Sets all counts to the given value, but does not remove any keys
- setAllowEmptyClusters(boolean) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- setArray(INDArray) - Method in class org.deeplearning4j.clustering.cluster.Point
-
- setAveragePointDistanceFromCenter(double) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- setBatchSize(int) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
Set the batch size for the optimizer
- setBatchSize(int) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- setBegin(int) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setBoundary(Cell) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setCenter(Point) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- setCenter(INDArray) - Method in class org.deeplearning4j.clustering.Cluster
-
- setCenterOfMass(INDArray) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setCluster(Cluster) - Method in class org.deeplearning4j.clustering.cluster.PointClassification
-
- setClusters(List<Cluster>) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- setClusters(List<Cluster>) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- setClusterSetInfo(ClusterSetInfo) - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
-
- setClustersInfos(Map<String, ClusterInfo>) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- setCol(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- setConf(NeuralNetConfiguration) - Method in interface org.deeplearning4j.nn.api.Model
-
Setter for the configuration
- setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setContentionTracing(boolean) - Static method in class org.deeplearning4j.util.ReflectionUtils
-
- setCorner(int, double) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- setCorner(INDArray) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- setCount(E, double) - Method in class org.deeplearning4j.berkeley.Counter
-
Set the count for the given key, clobbering any previous count.
- setCount(K, V, double) - Method in class org.deeplearning4j.berkeley.CounterMap
-
Sets the count for a particular (key, value) pair.
- setCounter(K, Counter<V>) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- setCumSize(int) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setCumSize(int) - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- setCurrent(int) - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
Set the position to be read.
- setCurrentIndex(long) - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Set the required current entry index.
- setD(int) - Method in class org.deeplearning4j.clustering.sptree.DataPoint
-
- setDefault(double) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- setDeflt(double) - Method in class org.deeplearning4j.berkeley.Counter
-
- setDirty(boolean) - Method in class org.deeplearning4j.berkeley.Counter
-
- setDistance(double) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- setDistanceFromCenter(double) - Method in class org.deeplearning4j.clustering.cluster.PointClassification
-
- setDistanceFunction(String) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- setDistanceFunction(Class<? extends Accumulation>) - Method in class org.deeplearning4j.clustering.ClusterSet
-
- setDistances(CounterMap<DataPoint, DataPoint>) - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
- setDistancesBetweenClustersCenters(Table<String, String, Double>) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- setEnd(int) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setError(double) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setFilters(PlotFilters) - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- setFinalMomentum(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setFinalMomentum(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setFirst(F) - Method in class org.deeplearning4j.berkeley.Pair
-
- setFirst(S) - Method in class org.deeplearning4j.berkeley.Triple
-
- setFirstKey(K) - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
-
- setGoldLabel(int) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setGradientFor(String, INDArray) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- setGradientFor(String, INDArray) - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
Update gradient for the given variable
- setHeadWord(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setHh(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- setHw(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- setId(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- setId(String) - Method in class org.deeplearning4j.clustering.cluster.Point
-
- setIndex(int) - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
-
- setIndex(int) - Method in class org.deeplearning4j.clustering.sptree.DataPoint
-
- setIndex(int) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- setIndex(int) - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- setIndex(int) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set the layer index.
- setIndex(int) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setIndex(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setInitialClusterCount(Integer) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- setInitialMomentum(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setInitialMomentum(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setInput(INDArray) - Method in interface org.deeplearning4j.nn.api.Layer
-
Get the layer input.
- setInput(INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setInput(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setInput(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
SetInput when img and words exist
- setInput(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Note that if input isn't null
and the neuralNets are null, this is a way
of initializing the neural network
- setInput(INDArray) - Method in class org.deeplearning4j.plot.PlotFilters
-
- setInputMiniBatchSize(int) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set current/last input mini-batch size.
Used for score and gradient calculations.
- setInputMiniBatchSize(int) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setInputMiniBatchSize(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setInvert(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setItems(List<DataPoint>) - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
- setIteration(int) - Method in class org.deeplearning4j.plot.iterationlistener.ActivationMeanIterationListener
-
- setIteration(int) - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- setIterationListener(IterationListener) - Method in class org.deeplearning4j.plot.Tsne
-
- setIterationsInfos(Map<Integer, IterationInfo>) - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationHistory
-
- setLabel(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- setLabel(String) - Method in class org.deeplearning4j.clustering.cluster.Point
-
- setLabel(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setLabels(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- setLabels(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setLayerGraphFilePath(String) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- setLayers(Layer[]) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setLayerWiseConfigurations(MultiLayerConfiguration) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setLeaf(boolean) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setLeft(KDTree.KDNode) - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- setLeft(VPTree.Node) - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- setListeners(IterationListener...) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set the iteration listeners for this layer.
- setListeners(Collection<IterationListener>) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set the iteration listeners for this layer.
- setListeners(Collection<IterationListener>) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setListeners(IterationListener...) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setListeners(Collection<IterationListener>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setListeners(IterationListener...) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setLogMetaInstability(double) - Method in class org.deeplearning4j.util.Viterbi
-
- setLogOfDiangnalTProb(double) - Method in class org.deeplearning4j.util.Viterbi
-
- setLogPCorrect(double) - Method in class org.deeplearning4j.util.Viterbi
-
- setLogPIncorrect(double) - Method in class org.deeplearning4j.util.Viterbi
-
- setLogStates(double) - Method in class org.deeplearning4j.util.Viterbi
-
- setLower(double) - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- setMask(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setMax(double) - Method in class org.deeplearning4j.util.SummaryStatistics
-
- setMaxCount(E, double) - Method in class org.deeplearning4j.berkeley.Counter
-
Set's the key's count to the maximum of the current count and val.
- setMaxIter(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setMaxIter(int) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setMaxIterations(int) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- setMaxPointDistanceFromCenter(double) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- setMean(double) - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- setMean(double) - Method in class org.deeplearning4j.util.SummaryStatistics
-
- setMetaStability(double) - Method in class org.deeplearning4j.util.Viterbi
-
- setMin(double) - Method in class org.deeplearning4j.util.SummaryStatistics
-
- setMinCount(E, double) - Method in class org.deeplearning4j.berkeley.Counter
-
Set's the key's count to the minimum of the current count and val.
- setMomentum(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setMomentum(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setNewLocation(boolean) - Method in class org.deeplearning4j.clustering.cluster.PointClassification
-
- setNorthEast(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setNorthWest(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setNumChildren(int) - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- setOptimizationPhaseCondition(ClusteringAlgorithmCondition) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- setOutputFile(File) - Method in class org.deeplearning4j.plot.iterationlistener.ActivationMeanIterationListener
-
- setOutputFile(File) - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- setParam(String, INDArray) - Method in interface org.deeplearning4j.nn.api.Model
-
Set the parameter with a new ndarray
- setParam(String, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setParam(String, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setParam(String, INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setParameters(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Sets parameters for the model.
- setParams(INDArray) - Method in interface org.deeplearning4j.nn.api.Model
-
Set the parameters for this model.
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Set the parameters for this model.
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Set the parameters for this model.
- setParams(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setParamTable(Map<String, INDArray>) - Method in interface org.deeplearning4j.nn.api.Model
-
Setter for the param table
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setParent(KDTree.KDNode) - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- setParent(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setParent(Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setParse(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setpCorrect(double) - Method in class org.deeplearning4j.util.Viterbi
-
- setPlot(INDArray) - Method in class org.deeplearning4j.plot.PlotFilters
-
- setPoint(INDArray) - Method in class org.deeplearning4j.clustering.sptree.DataPoint
-
- setPointDistanceFromCenterVariance(double) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- setPointDistancesFromCenter(Map<String, Double>) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- setPointDistribution(Map<String, String>) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- setPointLocationChange(AtomicInteger) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
-
- setPoints(List<Point>) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
- setPoints(List<INDArray>) - Method in class org.deeplearning4j.clustering.Cluster
-
- setPossibleLabels(INDArray) - Method in class org.deeplearning4j.util.Viterbi
-
- setPrediction(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- setProbabilityOfSuccess(double) - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
- setProperties(Object, Properties) - Static method in class org.deeplearning4j.util.Dl4jReflection
-
Sets the properties of the given object
- setRealMin(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setRealMin(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setRelTolx(double) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
Sets the tolerance of relative diff in function value.
- setRight(KDTree.KDNode) - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- setRight(VPTree.Node) - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- setScoreFor(INDArray) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- setScoreWithZ(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setScoreWithZ(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- setScoreWithZ(INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- setSecond(S) - Method in class org.deeplearning4j.berkeley.Pair
-
- setSecond(T) - Method in class org.deeplearning4j.berkeley.Triple
-
- setSecondKey(T) - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
-
- setSeed(long) - Method in class org.deeplearning4j.nn.conf.rng.DefaultRandom
-
Deprecated.
- setSimiarlityFunction(String) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setSize(int) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setSouthEast(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setSouthWest(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setStates(int) - Method in class org.deeplearning4j.util.Viterbi
-
- setStd(double) - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- setStepMax(double) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- setStrategyApplied(boolean) - Method in class org.deeplearning4j.clustering.algorithm.iteration.IterationInfo
-
- setSum(double) - Method in class org.deeplearning4j.util.SummaryStatistics
-
- setSwitchMomentumIteration(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setSwitchMomentumIteration(int) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setTags(List<String>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setTerminationCondition(ClusteringAlgorithmCondition) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- setThird(U) - Method in class org.deeplearning4j.berkeley.Triple
-
- setThreshold(double) - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- setTokens(List<String>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setTotalPointDistanceFromCenter(double) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterInfo
-
- setType(ClusteringOptimizationType) - Method in class org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimization
-
- setType(ClusteringStrategyType) - Method in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- setType(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setup(ClusteringStrategy) - Static method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- setup(int, String) - Static method in class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
-
- setup(int, String) - Static method in class org.deeplearning4j.clustering.algorithm.strategy.OptimisationStrategy
-
- setup(int, int, String) - Static method in class org.deeplearning4j.clustering.kmeans.KMeansClustering
-
- setup(int, double, String, boolean) - Static method in class org.deeplearning4j.clustering.kmeans.KMeansClustering
-
- setup(Configuration) - Method in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
-
- setupDirectory(String) - Static method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- setUpper(double) - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- setupSearchState(Pair<Gradient, Double>) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
Based on the gradient and score
setup a search state
- setupSearchState(Pair<Gradient, Double>) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
Setup the initial search state
- setupSearchState(Pair<Gradient, Double>) - Method in class org.deeplearning4j.optimize.solvers.LBFGS
-
- SetUtils - Class in org.deeplearning4j.util
-
- setValue(double) - Method in class org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimization
-
- setValue(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setValue(V) - Method in class org.deeplearning4j.util.MultiDimensionalMap.Entry
-
Replaces the value corresponding to this entry with the specified
value (optional operation).
- setVariables(List<String>) - Method in class org.deeplearning4j.plot.iterationlistener.PlotFiltersIterationListener
-
- setVector(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setWidth(int, double) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- setWidth(INDArray) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- setX(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- setY(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- setY(INDArray) - Method in class org.deeplearning4j.plot.Tsne
-
- SgdUpdater - Class in org.deeplearning4j.nn.updater
-
- SgdUpdater() - Constructor for class org.deeplearning4j.nn.updater.SgdUpdater
-
- sigma - Variable in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
- sigmoid(double) - Static method in class org.deeplearning4j.util.MathUtils
-
1 / 1 + exp(-x)
- similarityFunction(String) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- simpleHostname(String) - Static method in class org.deeplearning4j.util.StringUtils
-
Given a full hostname, return the word upto the first dot.
- size() - Method in class org.deeplearning4j.berkeley.Counter
-
The number of entries in the counter (not the total count -- use
totalCount() instead).
- size() - Method in class org.deeplearning4j.berkeley.CounterMap
-
The number of keys in this CounterMap (not the number of key-value entries
-- use totalSize() for that)
- size() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- size() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface
-
Number of elements in the queue.
- size() - Method in class org.deeplearning4j.clustering.kdtree.KDTree
-
The number of elements in the tree
- size() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- size() - Method in class org.deeplearning4j.util.Index
-
- size() - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
Returns the number of key-value mappings in this map.
- size() - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Returns the number of elements in this applyTransformToDestination (its cardinality).
- SizeComparator() - Constructor for class org.deeplearning4j.util.StringCluster.SizeComparator
-
- slope(double, double, double, double) - Method in class org.deeplearning4j.util.MathUtils
-
This returns the slope of the given points.
- SloppyMath - Class in org.deeplearning4j.berkeley
-
The class SloppyMath contains methods for performing basic
numeric operations.
- SloppyMath() - Constructor for class org.deeplearning4j.berkeley.SloppyMath
-
- slurpFile(File) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text in the given File.
- slurpFile(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text in the given file with the given encoding.
- slurpFile(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text in the given file
- slurpFileNoExceptions(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text in the given file with the given encoding.
- slurpFileNoExceptions(File) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text in the given File.
- slurpFileNoExceptions(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text in the given File.
- slurpGBFile(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- slurpGBFileNoExceptions(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- slurpGBURL(URL) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text at the given URL.
- slurpGBURLNoExceptions(URL) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text at the given URL.
- slurpReader(Reader) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text from the given Reader.
- slurpURL(URL, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text at the given URL.
- slurpURL(URL) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text at the given URL.
- slurpURL(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text at the given URL.
- slurpURLNoExceptions(URL, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text at the given URL.
- slurpURLNoExceptions(URL) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text at the given URL.
- slurpURLNoExceptions(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns all the text at the given URL.
- sm(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
Tests if a is smaller than b.
- SMALL - Static variable in class org.deeplearning4j.util.MathUtils
-
The small deviation allowed in double comparisons.
- solver - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- Solver - Class in org.deeplearning4j.optimize
-
Generic purpose solver
- Solver() - Constructor for class org.deeplearning4j.optimize.Solver
-
- Solver.Builder - Class in org.deeplearning4j.optimize
-
- sort() - Method in class org.deeplearning4j.util.StringCluster
-
- sortBy(int) - Method in class org.deeplearning4j.util.StringGrid
-
- sortColumnsByWordLikelihoodIncluded(int) - Method in class org.deeplearning4j.util.StringGrid
-
- sparsity(double) - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder.Builder
-
- sparsity - Variable in class org.deeplearning4j.nn.conf.layers.AutoEncoder
-
- sparsity(double) - Method in class org.deeplearning4j.nn.conf.layers.RBM.Builder
-
- sparsity - Variable in class org.deeplearning4j.nn.conf.layers.RBM
-
- split(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Splits on whitespace (\\s+).
- split(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Splits the given string using the given regex as delimiters.
- split(int, String) - Method in class org.deeplearning4j.util.StringGrid
-
- split(String) - Static method in class org.deeplearning4j.util.StringUtils
-
Split a string using the default separator
- split(String, char, char) - Static method in class org.deeplearning4j.util.StringUtils
-
Split a string using the given separator
- splitClusters(ClusterSet, ClusterSetInfo, List<Cluster>, double, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- splitClusters(ClusterSet, ClusterSetInfo, List<Cluster>, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- splitClustersWhereAverageDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- splitClustersWhereMaximumDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- splitInputs(INDArray, INDArray, List<Pair<INDArray, INDArray>>, List<Pair<INDArray, INDArray>>, double) - Static method in class org.deeplearning4j.util.InputSplit
-
- splitInputs(List<Pair<INDArray, INDArray>>, List<Pair<INDArray, INDArray>>, List<Pair<INDArray, INDArray>>, double) - Static method in class org.deeplearning4j.util.InputSplit
-
- splitMostPopulatedClusters(ClusterSet, ClusterSetInfo, int, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- splitMostSpreadOutClusters(ClusterSet, ClusterSetInfo, int, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- splitOnCharWithQuoting(String, char, char, char) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
This function splits the String s into multiple Strings using the
splitChar.
- SpTree - Class in org.deeplearning4j.clustering.sptree
-
- SpTree(SpTree, INDArray, INDArray, INDArray, Set<INDArray>, String) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
-
- SpTree(INDArray, Set<INDArray>, String) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
-
- SpTree(SpTree, INDArray, INDArray, INDArray, Set<INDArray>) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
-
- SpTree(INDArray, Set<INDArray>) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
-
- SpTree(INDArray) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
-
- squaredLoss(double[], double[], double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
This will return the squared loss of the given
points
- ssError(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
How much of the variance is NOT explained by the regression
- ssReg(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
How much of the variance is explained by the regression
- ssTotal(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Total variance in target attribute
- start() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
-
- start() - Method in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- STATE_KEY_PREV_ACTIVATION - Static variable in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- STATE_KEY_PREV_ACTIVATION - Static variable in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- STATE_KEY_PREV_MEMCELL - Static variable in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- STATE_TRACKER_CONNECTION_STRING - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
-
- stateMap - Variable in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
stateMap stores the INDArrays needed to do rnnTimeStep() forward pass.
- stats() - Method in class org.deeplearning4j.eval.Evaluation
-
- step(INDArray, INDArray, double) - Method in interface org.deeplearning4j.optimize.api.StepFunction
-
Step with the given parameters
- step(INDArray, INDArray) - Method in interface org.deeplearning4j.optimize.api.StepFunction
-
Step with no parameters
- step() - Method in interface org.deeplearning4j.optimize.api.StepFunction
-
- step - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- step(INDArray, INDArray, double) - Method in class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
-
Does x = x + stepSize * line
- step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
-
- step() - Method in class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
-
- step(INDArray, INDArray, double) - Method in class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
-
- step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
-
- step() - Method in class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
-
- step(INDArray, INDArray, double) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
-
- step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
-
- step() - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
-
- step(INDArray, INDArray, double) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
-
- step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
-
- step() - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
-
- step(INDArray, int) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
An individual iteration
- step(INDArray, int) - Method in class org.deeplearning4j.plot.Tsne
-
An individual iteration
- stepFunction(StepFunction) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- stepFunction - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- StepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions
-
Custom step function for line search.
- StepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.StepFunction
-
- StepFunction - Interface in org.deeplearning4j.optimize.api
-
Custom step function for line search
- stepFunction - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- StepFunctions - Class in org.deeplearning4j.optimize.stepfunctions
-
- StepFunctions() - Constructor for class org.deeplearning4j.optimize.stepfunctions.StepFunctions
-
- stepMax - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- StochasticGradientDescent - Class in org.deeplearning4j.optimize.solvers
-
Stochastic Gradient Descent
Standard fix step size
No line search
- StochasticGradientDescent(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.StochasticGradientDescent
-
- StochasticGradientDescent(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.StochasticGradientDescent
-
- StochasticHessianFree - Class in org.deeplearning4j.optimize.solvers
-
Hessian Free Optimization
by Ryan Kiros http://www.cs.toronto.edu/~rkiros/papers/shf13.pdf
- StochasticHessianFree(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.StochasticHessianFree
-
- StochasticHessianFree(NeuralNetConfiguration, StepFunction, Collection<IterationListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.StochasticHessianFree
-
- stopLyingIteration(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- stopLyingIteration - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- stopLyingIteration(int) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- stopLyingIteration - Variable in class org.deeplearning4j.plot.Tsne
-
- stride(int...) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- stride - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- stride(int...) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- stride - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- string2long(String) - Static method in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix
-
Convert a string to long.
- StringCluster - Class in org.deeplearning4j.util
-
Clusters strings based on fingerprint: for example
Two words and TWO words or WORDS TWO would be put together
- StringCluster(List<String>) - Constructor for class org.deeplearning4j.util.StringCluster
-
- StringCluster.SizeComparator - Class in org.deeplearning4j.util
-
- StringGrid - Class in org.deeplearning4j.util
-
String matrix
- StringGrid(StringGrid) - Constructor for class org.deeplearning4j.util.StringGrid
-
- StringGrid(String, int) - Constructor for class org.deeplearning4j.util.StringGrid
-
- StringGrid(String, Collection<String>) - Constructor for class org.deeplearning4j.util.StringGrid
-
- stringifyException(Throwable) - Static method in class org.deeplearning4j.util.StringUtils
-
Make a string representation of the exception.
- stringSimilarity(String...) - Static method in class org.deeplearning4j.util.MathUtils
-
Calculate string similarity with tfidf weights relative to each character
frequency and how many times a character appears in a given string
- stringToProperties(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
This method converts a comma-separated String (with whitespace
optionally allowed after the comma) representing properties
to a Properties object.
- stringToURI(String[]) - Static method in class org.deeplearning4j.util.StringUtils
-
- StringUtils - Class in org.deeplearning4j.berkeley
-
StringUtils is a class for random String things.
- StringUtils - Class in org.deeplearning4j.util
-
General string utils
- StringUtils() - Constructor for class org.deeplearning4j.util.StringUtils
-
- StringUtils.TraditionalBinaryPrefix - Enum in org.deeplearning4j.util
-
The traditional binary prefixes, kilo, mega, ..., exa,
which can be represented by a 64-bit integer.
- stripDuplicateRows() - Method in class org.deeplearning4j.util.StringGrid
-
- stripNonAlphaNumerics(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- subDivide() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
Create four children
which fully divide this cell
into four quads of equal area
- subDivide() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
Subdivide the node in to
4 children
- SubsampleLayerFactory - Class in org.deeplearning4j.nn.layers.factory
-
- SubsampleLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.SubsampleLayerFactory
-
- SubsampleParamInitializer - Class in org.deeplearning4j.nn.params
-
- SubsampleParamInitializer() - Constructor for class org.deeplearning4j.nn.params.SubsampleParamInitializer
-
- SubsamplingLayer - Class in org.deeplearning4j.nn.conf.layers
-
Subsampling layer also referred to as pooling in convolution neural nets
Supports the following pooling types:
MAX
AVG
NON
- SubsamplingLayer - Class in org.deeplearning4j.nn.layers.convolution.subsampling
-
Subsampling layer.
- SubsamplingLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- SubsamplingLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- SubsamplingLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- SubsamplingLayer.PoolingType - Enum in org.deeplearning4j.nn.conf.layers
-
- sum(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the sum of the given array.
- SummaryStatistics - Class in org.deeplearning4j.util
-
- summaryStats(INDArray) - Static method in class org.deeplearning4j.util.SummaryStatistics
-
- summaryStatsString(INDArray) - Static method in class org.deeplearning4j.util.SummaryStatistics
-
- sumOfMeanDifferences(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Used for calculating top part of simple regression for
beta 1
- sumOfMeanDifferencesOnePoint(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Used for calculating top part of simple regression for
beta 1
- sumOfProducts(double[]...) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the sum of products for the given
numbers.
- sumOfSquares(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the sum of squares for the given vector.
- swap(int, int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- swap(int, int) - Method in class org.deeplearning4j.util.StringGrid
-
- switchMomentumIteration - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- switchMomentumIteration - Variable in class org.deeplearning4j.plot.Tsne
-
- symbol - Variable in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix
-
- symmetrized(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Symmetrize the value matrix
- tags() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- terminate(double, double, Object[]) - Method in interface org.deeplearning4j.optimize.api.TerminationCondition
-
Whether to terminate based on the given metadata
- terminate(double, double, Object[]) - Method in class org.deeplearning4j.optimize.terminations.EpsTermination
-
- terminate(double, double, Object[]) - Method in class org.deeplearning4j.optimize.terminations.Norm2Termination
-
- terminate(double, double, Object[]) - Method in class org.deeplearning4j.optimize.terminations.ZeroDirection
-
- terminationCondition - Variable in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- TerminationCondition - Interface in org.deeplearning4j.optimize.api
-
Created by agibsonccc on 12/24/14.
- terminationConditions - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- TerminationConditions - Class in org.deeplearning4j.optimize.terminations
-
Created by agibsonccc on 12/24/14.
- TerminationConditions() - Constructor for class org.deeplearning4j.optimize.terminations.TerminationConditions
-
- TestDataSetIterator - Class in org.deeplearning4j.datasets.test
-
Track number of times the dataset iterator has been called
- TestDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- tf(int) - Static method in class org.deeplearning4j.util.MathUtils
-
Term frequency: 1+ log10(count)
- tfidf(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
Return td * idf
- theta(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- thread(Iterator<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
-
Executes calls to next() in a different thread
- times(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the product of all numbers in the given array.
- timeSeriesLength(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
+ * Time series length
+ * @param timeSeriesLength
+ * @return
+
- TimeSeriesUtils - Class in org.deeplearning4j.util
-
Basic time series utils
- TimeSeriesUtils() - Constructor for class org.deeplearning4j.util.TimeSeriesUtils
-
- title - Variable in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
-
- title - Variable in class org.deeplearning4j.plot.FilterRenderer
-
Deprecated.
- toArray() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- toArray(T[]) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- toArray() - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Returns an array containing all of the elements in this applyTransformToDestination.
- toArray(T[]) - Method in class org.deeplearning4j.util.MultiDimensionalSet
-
Returns an array containing all of the elements in this applyTransformToDestination; the
runtime type of the returned array is that of the specified array.
- toBufferedImage(Image) - Static method in class org.deeplearning4j.util.ImageLoader
-
Converts a given Image into a BufferedImage
- toBufferedImageRGB(INDArray) - Static method in class org.deeplearning4j.util.ImageLoader
-
Convert the given image to an rgb image
- toByteArray(Serializable) - Static method in class org.deeplearning4j.util.SerializationUtils
-
Converts the given object to a byte array
- toCSV() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Outputs the ConfusionMatrix as comma-separated values for easy import into spreadsheets
- toDecimal(String) - Static method in class org.deeplearning4j.util.MathUtils
-
This will convert the given binary string to a decimal based
integer
- toHTML() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Outputs Confusion Matrix in an HTML table.
- toImage(INDArray) - Static method in class org.deeplearning4j.util.ImageLoader
-
- toJson() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- toJson() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Return this configuration as json
- tolerance(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- tolerance - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- tolerance(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- tolerance - Variable in class org.deeplearning4j.plot.Tsne
-
- toLines() - Method in class org.deeplearning4j.util.StringGrid
-
- toLogSpace() - Method in class org.deeplearning4j.berkeley.Counter
-
- toPoints(List<INDArray>) - Static method in class org.deeplearning4j.clustering.cluster.Point
-
- toString() - Method in class org.deeplearning4j.berkeley.Counter
-
Returns a string representation with the keys ordered by decreasing
counts.
- toString(int) - Method in class org.deeplearning4j.berkeley.Counter
-
Returns a string representation which includes no more than the
maxKeysToPrint elements with largest counts.
- toString(int, boolean) - Method in class org.deeplearning4j.berkeley.Counter
-
Returns a string representation which includes no more than the
maxKeysToPrint elements with largest counts and optionally prints
one element per line.
- toString(int) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- toString() - Method in class org.deeplearning4j.berkeley.CounterMap
-
- toString(Collection<String>) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- toString() - Method in class org.deeplearning4j.berkeley.Pair
-
- toString() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
Returns a representation of the queue in decreasing priority order.
- toString(int, boolean) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
Returns a representation of the queue in decreasing priority order,
displaying at most maxKeysToPrint elements and optionally printing
one element per line.
- toString() - Method in class org.deeplearning4j.berkeley.Triple
-
- toString() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
- toString() - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- toString() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- toString() - Method in class org.deeplearning4j.nn.conf.rng.DefaultRandom
-
Deprecated.
- toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.DefaultStepFunction
-
- toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.GradientStepFunction
-
- toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeDefaultStepFunction
-
- toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeGradientStepFunction
-
- toString() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- toString() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- toString() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- toString() - Method in class org.deeplearning4j.util.Index
-
- toString() - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
- toString() - Method in class org.deeplearning4j.util.SummaryStatistics
-
- toStringSortedByKeys() - Method in class org.deeplearning4j.berkeley.Counter
-
- toStringTabSeparated() - Method in class org.deeplearning4j.berkeley.Counter
-
- totalCount() - Method in class org.deeplearning4j.berkeley.Counter
-
Finds the total of all counts in the counter.
- totalCount() - Method in class org.deeplearning4j.berkeley.CounterMap
-
Returns the total of all counts in sub-counters.
- totalExamples() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- totalExamples - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- totalExamples() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- totalExamples() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
The total number of examples
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Total examples in the iterator
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Total examples in the iterator
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.canova.RecordReaderDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- totalOutcomes() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
The number of labels for a dataset
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
The number of labels for the dataset
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
The number of labels for the dataset
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- totalSize() - Method in class org.deeplearning4j.berkeley.CounterMap
-
Returns the total number of (key, value) entries in the CounterMap (not
their total counts).
- toYaml() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- toYaml() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Return this configuration as json
- trainingFileLabelsFilename_unzipped - Static variable in class org.deeplearning4j.base.MnistFetcher
-
- trainingFilesFilename_unzipped - Static variable in class org.deeplearning4j.base.MnistFetcher
-
- Transform(Iterator<S>) - Constructor for class org.deeplearning4j.berkeley.Iterators.Transform
-
- transform(S) - Method in class org.deeplearning4j.berkeley.Iterators.Transform
-
- TransformingIterator(Iterator<I>, MyMethod<I, O>) - Constructor for class org.deeplearning4j.berkeley.Iterators.TransformingIterator
-
- transpose() - Method in interface org.deeplearning4j.nn.api.Layer
-
Return a transposed copy of the weights/bias
(this means reverse the number of inputs and outputs on the weights)
- transpose() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
-
- transpose() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- transpose() - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
-
- transpose() - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- transpose() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- Tree - Class in org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive
-
Tree for a recursive neural tensor network
based on Socher et al's work.
- Tree(Tree) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Clone constructor (all but the children)
- Tree(Tree, List<String>) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- Tree(List<String>) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- TreeMapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory.TreeMapFactory
-
- treeSet() - Static method in class org.deeplearning4j.util.MultiDimensionalSet
-
- trim(String, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
Returns s if it's at most maxWidth chars, otherwise chops right side to fit.
- trim(Object, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- Triple<S,T,U> - Class in org.deeplearning4j.berkeley
-
- Triple(S, T, U) - Constructor for class org.deeplearning4j.berkeley.Triple
-
- trueNegatives() - Method in class org.deeplearning4j.eval.Evaluation
-
True negatives: correctly rejected
- truePositives() - Method in class org.deeplearning4j.eval.Evaluation
-
True positives: correctly rejected
- truncate(int, int, int) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
This returns a string from decimal digit smallestDigit to decimal digit
biggest digit.
- Tsne - Class in org.deeplearning4j.plot
-
Tsne calculation
- Tsne() - Constructor for class org.deeplearning4j.plot.Tsne
-
- Tsne(int, double, double, double, double, int, boolean, boolean, int, double, double, boolean, double, double) - Constructor for class org.deeplearning4j.plot.Tsne
-
- Tsne.Builder - Class in org.deeplearning4j.plot
-
- type - Variable in class org.deeplearning4j.clustering.algorithm.strategy.BaseClusteringStrategy
-
- type() - Method in interface org.deeplearning4j.nn.api.Layer
-
Returns the layer type
- type() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
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- type() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
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- type() - Method in class org.deeplearning4j.nn.layers.recurrent.GRU
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- type() - Method in class org.deeplearning4j.nn.layers.recurrent.ImageLSTM
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- type() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- typeForFactory(NeuralNetConfiguration) - Static method in class org.deeplearning4j.nn.layers.factory.LayerFactories
-
Get the type for the layer factory
- validateInput() - Method in interface org.deeplearning4j.nn.api.Model
-
Validate the input
- validateInput() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- validateInput() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- validateInput() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- value() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- value - Variable in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix
-
- valueOf(String) - Static method in enum org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimizationType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategyType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.api.Layer.Type
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.api.OptimizationAlgorithm
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionLayer.PoolingType
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Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.RBM.HiddenUnit
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.RBM.VisibleUnit
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.SubsamplingLayer.PoolingType
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Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.Updater
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.weights.WeightInit
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix
-
Returns the enum constant of this type with the specified name.
- valueOf(char) - Static method in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix
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- values() - Static method in enum org.deeplearning4j.clustering.algorithm.optimisation.ClusteringOptimizationType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.clustering.algorithm.strategy.ClusteringStrategyType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.api.Layer.Type
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.api.OptimizationAlgorithm
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionLayer.PoolingType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.RBM.HiddenUnit
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.RBM.VisibleUnit
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.SubsamplingLayer.PoolingType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.Updater
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.weights.WeightInit
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Method in class org.deeplearning4j.util.MultiDimensionalMap
-
Returns a
Collection view of the values contained in this map.
- values() - Static method in enum org.deeplearning4j.util.StringUtils.TraditionalBinaryPrefix
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- variables - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- variables() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- variance(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
- VarianceVariationCondition - Class in org.deeplearning4j.clustering.algorithm.condition
-
- VarianceVariationCondition(Condition, int) - Constructor for class org.deeplearning4j.clustering.algorithm.condition.VarianceVariationCondition
-
- varianceVariationLessThan(double, int) - Static method in class org.deeplearning4j.clustering.algorithm.condition.VarianceVariationCondition
-
- vector() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- vectorize() - Method in class org.deeplearning4j.datasets.vectorizer.ImageVectorizer
-
- vectorize() - Method in interface org.deeplearning4j.datasets.vectorizer.Vectorizer
-
Vectorizes the input source in to a dataset
- Vectorizer - Interface in org.deeplearning4j.datasets.vectorizer
-
A Vectorizer at its essence takes an input source
and converts it to a matrix for neural network consumption.
- vectorLength(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Returns the vector length (sqrt(sum(x_i))
- VISIBLE_BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.PretrainParamInitializer
-
- VISIBLE_BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.RecursiveParamInitializer
-
- visibleUnit(RBM.VisibleUnit) - Method in class org.deeplearning4j.nn.conf.layers.RBM.Builder
-
- visibleUnit - Variable in class org.deeplearning4j.nn.conf.layers.RBM
-
- Viterbi - Class in org.deeplearning4j.util
-
Based on the impl from:
https://gist.github.com/rmcgibbo/3915977
- Viterbi(INDArray) - Constructor for class org.deeplearning4j.util.Viterbi
-
The possible outcomes for the chain.
- VPTree - Class in org.deeplearning4j.clustering.vptree
-
Vantage point tree implementation
- VPTree(INDArray, String, boolean) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(List<DataPoint>, CounterMap<DataPoint, DataPoint>, String, boolean) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(List<DataPoint>, String, boolean) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(INDArray, String) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(List<DataPoint>, CounterMap<DataPoint, DataPoint>, String) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(List<DataPoint>, String) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(INDArray) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(List<DataPoint>, CounterMap<DataPoint, DataPoint>) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(List<DataPoint>) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree.Node - Class in org.deeplearning4j.clustering.vptree
-