- 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(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) - 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.OutputLayer
-
- activate(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
- activate() - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
- 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(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- 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.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) - 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) - Method in class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
-
- backprop(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- backprop(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- backprop(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- backprop(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- backprop(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
-
- backprop(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- backprop(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.UnitVarianceProcessor
-
- backprop(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanAndUnitVariancePreProcessor
-
- backprop(INDArray) - 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.convolution.ConvolutionLayer
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- backpropGradient(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- 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
-
- 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
-
- 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.LSTM
-
- 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.LSTMParamInitializer
-
- 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.Layer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.LSTM.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.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.BasePretrainNetwork.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.Layer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.LSTM.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.OutputLayer.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(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.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.LSTM
-
- 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.LSTM
-
- 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
- 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.OutputLayer
-
- clear() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- 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.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.layers.OutputLayer
-
- 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.OutputLayer
-
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.
- ConvolutionDownSampleLayer - Class in org.deeplearning4j.nn.conf.layers
-
Deprecated.
- ConvolutionDownSampleLayer() - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionDownSampleLayer
-
Deprecated.
- 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.BasePretrainNetwork.Builder
-
- customLossFunction(String) - Method in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- customLossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
-
- customLossFunction(String) - Method in class org.deeplearning4j.nn.conf.layers.OutputLayer.Builder
-
- 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.OutputLayer
-
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.OutputLayer
-
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(int) - 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() - 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.rbm.RBM
-
Note: k is the first input hidden params.
- fit(DataSetIterator) - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
- fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
Fit the model
- fit(DataSet) - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
Fit the model
- fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
Fit the model
- fit(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
Fit the model to the given data
- fit(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- 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.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.OutputLayer
-
- getLabels() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- 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.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- gradient() - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
Gets the gradient from one training iteration
- gradient() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- 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.OutputLayer
-
- 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
-
- 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
-
- 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
-
- 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.LSTMParamInitializer
-
- init(Map<String, INDArray>, NeuralNetConfiguration, Configuration) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- 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.LSTMLayerFactory
-
- 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.LSTMParamInitializer
-
- 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.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.layers.OutputLayer
-
- 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.OutputLayer
-
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.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.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
-
- lossFunction(LossFunctions.LossFunction) - Method in class org.deeplearning4j.nn.conf.layers.OutputLayer.Builder
-
- 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
-
- LSTM - Class in org.deeplearning4j.nn.conf.layers
-
LSTM recurrent net.
- LSTM - Class in org.deeplearning4j.nn.layers.recurrent
-
LSTM recurrent net.
- LSTM(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- LSTM(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- LSTM.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- LSTMLayerFactory - Class in org.deeplearning4j.nn.layers.factory
-
LSTM layer initializer
- LSTMLayerFactory(Class<? extends Layer>) - Constructor for class org.deeplearning4j.nn.layers.factory.LSTMLayerFactory
-
- LSTMParamInitializer - Class in org.deeplearning4j.nn.params
-
LSTM Parameters.
- LSTMParamInitializer() - Constructor for class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- 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.OutputLayer
-
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
- 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.OutputLayer
-
Returns the predictions for each example in the dataset
- predict(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
Prediction with beam search
- 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.multilayer.MultiLayerNetwork
-
- preOutput(INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- prependToEach(String, int) - Method in class org.deeplearning4j.util.StringGrid
-
- preProcess(INDArray) - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor
-
Pre preProcess input/activations for a multi layer network
- preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
-
- preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
-
- preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.UnitVarianceProcessor
-
- preProcess(INDArray) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanAndUnitVariancePreProcessor
-
- preProcess(INDArray) - 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.LSTMParamInitializer
-
- 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
-
- 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(int) - 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.LSTM
-
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.OutputLayer
-
- 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.convolution.subsampling.SubsamplingLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
Set the parameters for this model.
- 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.BasePretrainNetwork
-
- setScoreWithZ(INDArray) - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
- 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_TRACKER_CONNECTION_STRING - Static variable in interface org.deeplearning4j.nn.conf.DeepLearningConfigurable
-
- 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.layers.ConvolutionDownSampleLayer
-
Deprecated.
- 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.LSTM
-
- 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
-
- type() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.RecursiveAutoEncoder
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- 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
-
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
-
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
-
- 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
-