- 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
-
- activate() - Method in class org.deeplearning4j.nn.HiddenLayer
-
Trigger an activation with the last specified input
- activate(DoubleMatrix) - Method in class org.deeplearning4j.nn.HiddenLayer
-
Initialize the layer with the given input
and return the activation for this layer
given this input
- activation - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- ActivationFunction - Interface in org.deeplearning4j.nn.activation
-
An activation function for a hidden layer for neural networks
- 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(LogisticRegressionGradient) - Method in class org.deeplearning4j.nn.gradient.LogisticRegressionGradient
-
Sums this gradient with the given one
- add(NeuralNetworkGradient) - Method in class org.deeplearning4j.nn.gradient.NeuralNetworkGradient
-
Adds the given gradient and this one together
- Add - Class in org.deeplearning4j.transformation
-
- Add() - Constructor for class org.deeplearning4j.transformation.Add
-
- add(DoubleMatrix, DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- 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.
- addRow(DataSet, int) - Method in class org.deeplearning4j.datasets.DataSet
-
- AddScalar - Class in org.deeplearning4j.transformation
-
- AddScalar(double) - Constructor for class org.deeplearning4j.transformation.AddScalar
-
- addToConfusion(int, int) - Method in class org.deeplearning4j.eval.Evaluation
-
Adds to the confusion matrix
- adjustedrSquared(double, int, int) - Static method in class org.deeplearning4j.util.MathUtils
-
This calculates the adjusted r^2 including degrees of freedom.
- allMatches(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- appendTo(String, File) - Static method in class org.deeplearning4j.util.FileOperations
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.distancefunction.CosineSimilarity
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.distancefunction.EuclideanDistance
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.distancefunction.ManhattanDistance
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.nn.activation.HardTanh
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.nn.activation.Sigmoid
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.nn.activation.Tanh
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.Add
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.AddScalar
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.Divide
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.ExpTransform
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.LogTransform
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.Multiply
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.MultiplyScalar
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.PowScale
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.ScalarMatrixTransform
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.SqrtScalar
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.Subtract
-
- apply(DoubleMatrix) - Method in class org.deeplearning4j.transformation.SubtractScalar
-
- applyDerivative(DoubleMatrix) - Method in interface org.deeplearning4j.nn.activation.ActivationFunction
-
Applies the derivative of this function
- applyDerivative(DoubleMatrix) - Method in class org.deeplearning4j.nn.activation.HardTanh
-
- applyDerivative(DoubleMatrix) - Method in class org.deeplearning4j.nn.activation.Sigmoid
-
- applyDerivative(DoubleMatrix) - Method in class org.deeplearning4j.nn.activation.Tanh
-
- applyTransforms() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- 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
-
- 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
-
- ArrayUtil - Class in org.deeplearning4j.util
-
- ArrayUtil() - Constructor for class org.deeplearning4j.util.ArrayUtil
-
- 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.
- asDecoder(BaseMultiLayerNetwork) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Set as decoder for another neural net
designed for encoding (primary output is
encoding input)
- asList() - Method in class org.deeplearning4j.datasets.DataSet
-
- 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
-
- assertIntMatrix(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- asType(Class<E>) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
-
- avg(DoubleMatrix...) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- 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.
- CDBN - Class in org.deeplearning4j.dbn
-
Continuous Deep Belief Network.
- CDBN() - Constructor for class org.deeplearning4j.dbn.CDBN
-
- CDBN(int, int[], int, int, RandomGenerator, DoubleMatrix, DoubleMatrix) - Constructor for class org.deeplearning4j.dbn.CDBN
-
- CDBN(int, int[], int, int, RandomGenerator) - Constructor for class org.deeplearning4j.dbn.CDBN
-
- CDBN.Builder - Class in org.deeplearning4j.dbn
-
- CDBN.Builder() - Constructor for class org.deeplearning4j.dbn.CDBN.Builder
-
- 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
- classCount(int) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the number of times the given label
has actually occurred
- classify(DoubleMatrix) - Method in class org.deeplearning4j.clustering.KMeansClustering
-
- clazz - Variable in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
-
- clazz - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
-
- clear() - Method in class org.deeplearning4j.berkeley.Counter
-
- clone() - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
Returns a clone of this priority queue.
- clone() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- clone() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- clone() - Method in class org.deeplearning4j.nn.HiddenLayer
-
- clone() - Method in class org.deeplearning4j.nn.LogisticRegression
-
- clone() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- close() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawMnistGreyScale
-
- close() - Method in class org.deeplearning4j.plot.FilterRenderer
-
- columnNormalizeBySum(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- columnStd(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
Calculates the column wise standard deviations
of the matrix
- columnStdDeviation(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- columnWiseMean(DoubleMatrix, int) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- combination(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the combination of n choose r
- 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
-
- complainAboutMissMatchedMatrices(DoubleMatrix, DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- computeDxs() - Method in class org.deeplearning4j.clustering.KMeansClustering
-
For each features in KMeans#initFeatures, compute D(x), the
distance between x and the nearest center that has already been chosen.
- computeHistogramBucketIndex(double, double, double, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
- computeHistogramBucketIndexAlt(double, double, double, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
This is faster but produces rounding errors
- 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
-
- ConfusionMatrix<T extends Comparable<? super T>> - Class in org.deeplearning4j.eval
-
This data structure provides an easy way to build and output a confusion matrix.
- ConfusionMatrix() - Constructor for class org.deeplearning4j.eval.ConfusionMatrix
-
Creates an empty confusion Matrix
- ConfusionMatrix(ConfusionMatrix<T>) - Constructor for class org.deeplearning4j.eval.ConfusionMatrix
-
Creates a new ConfusionMatrix initialized with the contents of another ConfusionMatrix.
- 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
-
- contrastiveDivergence(double, int, DoubleMatrix) - Method in class org.deeplearning4j.rbm.RBM
-
Contrastive divergence revolves around the idea
of approximating the log likelihood around x1(input) with repeated sampling.
- convertListPairs(List<Pair<DoubleMatrix, DoubleMatrix>>) - Method in class org.deeplearning4j.base.LFWLoader
-
- 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
- copy() - Method in class org.deeplearning4j.datasets.DataSet
-
- correlation(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Returns the correlation coefficient of two double vectors.
- cosine(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- cosineSim(DoubleMatrix, DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- CosineSimilarity - Class in org.deeplearning4j.distancefunction
-
- CosineSimilarity(DoubleMatrix) - Constructor for class org.deeplearning4j.distancefunction.CosineSimilarity
-
- 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
-
- CRBM - Class in org.deeplearning4j.rbm
-
Continuous Restricted Boltzmann Machine
- CRBM() - Constructor for class org.deeplearning4j.rbm.CRBM
-
- CRBM(DoubleMatrix, int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, double, RealDistribution) - Constructor for class org.deeplearning4j.rbm.CRBM
-
- CRBM.Builder - Class in org.deeplearning4j.rbm
-
- CRBM.Builder() - Constructor for class org.deeplearning4j.rbm.CRBM.Builder
-
- createAppendingOutputStream(File) - Static method in class org.deeplearning4j.util.FileOperations
-
- createInputMatrix(int) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- createLayer(DoubleMatrix, int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, int) - Method in class org.deeplearning4j.dbn.CDBN
-
- createLayer(DoubleMatrix, int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, int) - Method in class org.deeplearning4j.dbn.DBN
-
- createLayer(DoubleMatrix, int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Creates a layer depending on the index.
- createLayer(DoubleMatrix, int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, int) - Method in class org.deeplearning4j.sda.StackedDenoisingAutoEncoder
-
- createNetworkLayers(int) - Method in class org.deeplearning4j.dbn.CDBN
-
- createNetworkLayers(int) - Method in class org.deeplearning4j.dbn.DBN
-
- createNetworkLayers(int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- createNetworkLayers(int) - Method in class org.deeplearning4j.sda.StackedDenoisingAutoEncoder
-
- createOutputMatrix(int) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- createOutputVector(int) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- curr - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- 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
-
- cursor() - Method in interface org.deeplearning4j.datasets.iterator.DataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.test.TestDataSetIterator
-
- generateHistogramBuckets(DoubleMatrix, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
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.datasets.DataSet
-
- getActivation() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getActivation() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getActivationFunction() - Method in class org.deeplearning4j.nn.HiddenLayer
-
- getActualTotal(T) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Computes the total number of times the class actually appeared in the data.
- getAllImagesAsMatrix() - Method in class org.deeplearning4j.base.LFWLoader
-
- getAllImagesAsMatrix(int) - Method in class org.deeplearning4j.base.LFWLoader
-
- getB() - Method in class org.deeplearning4j.nn.HiddenLayer
-
- getB() - Method in class org.deeplearning4j.nn.LogisticRegression
-
- getbGradient() - Method in class org.deeplearning4j.nn.gradient.LogisticRegressionGradient
-
- getCentroids() - Method in class org.deeplearning4j.clustering.KMeansClustering
-
- getClasses() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Gives the set of all classes in the confusion matrix.
- getCols() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Number of columns per image.
- getColumnMeans() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getColumnStds() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getColumnSums() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getCorruptedInput(DoubleMatrix, double) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
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
-
- getCurrentIndex() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
The current entry index.
- getDataFor(int) - Method in class org.deeplearning4j.base.LFWLoader
-
- getDeflt() - Method in class org.deeplearning4j.berkeley.Counter
-
- getDist() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getDist() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getDist() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getDist() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- 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
-
- getErrors() - Method in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- getErrorTolerance() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getFaces(int) - Static method in class org.deeplearning4j.base.DeepLearningTest
-
LFW Dataset: pick first num faces
- getFaces() - Method in class org.deeplearning4j.base.DeepLearningTest
-
LFW Dataset: pick all faces
- getFacesMatrix() - Static method in class org.deeplearning4j.base.DeepLearningTest
-
LFW Dataset: pick all faces
- getFanIn() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getFanIn() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getFirst(int) - Method in class org.deeplearning4j.base.LFWLoader
-
Get the first num found images
- getFirst() - Method in class org.deeplearning4j.berkeley.Pair
-
- getFirst() - Method in class org.deeplearning4j.berkeley.Triple
-
- getFirstFaces(int) - Static method in class org.deeplearning4j.base.DeepLearningTest
-
LFW Dataset: pick first num faces
- getGradient(Object[]) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
- getGradient(Object[], double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Gets the multi layer gradient for this network.
- getGradient(double) - Method in class org.deeplearning4j.nn.LogisticRegression
-
Gets the gradient from one training iteration
- getGradient(Object[]) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getGradient(Object[]) - Method in class org.deeplearning4j.rbm.RBM
-
- getGradients() - Method in class org.deeplearning4j.nn.gradient.MultiLayerGradient
-
- gethBias() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- gethBias() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- gethBiasGradient() - Method in class org.deeplearning4j.nn.gradient.NeuralNetworkGradient
-
- getHeaderSize() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
- getHeaderSize() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
- getHiddenBiasTransforms() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getHiddenLayerSizes() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getHiddenLayerSizes() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getHiddenValues(DoubleMatrix) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
- getIfNotExists() - Method in class org.deeplearning4j.base.LFWLoader
-
- getImage() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawMnistGreyScale
-
- getImage() - Method in class org.deeplearning4j.plot.FilterRenderer
-
- 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
-
- getInitialStepSize() - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- getInput() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getInput() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getInput() - Method in class org.deeplearning4j.nn.HiddenLayer
-
- getInput() - Method in class org.deeplearning4j.nn.LogisticRegression
-
- getInput() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getIris() - Static method in class org.deeplearning4j.base.DeepLearningTest
-
- getIris(int) - Static method in class org.deeplearning4j.base.DeepLearningTest
-
- getL2() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getL2() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getL2() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getL2() - Method in class org.deeplearning4j.nn.LogisticRegression
-
- getL2() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getLabels() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
- getLabels() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getLabels() - Method in class org.deeplearning4j.nn.LogisticRegression
-
- getLayers() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getLearningRateUpdate() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getLogLayer() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getLogLayer() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getLogRegGradient() - Method in class org.deeplearning4j.nn.gradient.MultiLayerGradient
-
- 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
-
- getMaxIterations() - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- getMnistExample(int) - Static method in class org.deeplearning4j.base.DeepLearningTest
-
Gets an mnist example as an input, label pair.
- getMnistExampleBatch(int) - Static method in class org.deeplearning4j.base.DeepLearningTest
-
Gets an mnist example as an input, label pair.
- getMnistExampleBatches(int, int) - Method in class org.deeplearning4j.base.DeepLearningTest
-
Gets an mnist example as an input, label pair.
- getMomentum() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getMomentum() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getMomentum() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getMomentum() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getnHidden() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getnHidden() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getnIn() - Method in class org.deeplearning4j.nn.HiddenLayer
-
- getnIn() - Method in class org.deeplearning4j.nn.LogisticRegression
-
- getnIns() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getnIns() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getnLayers() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getnLayers() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getnOut() - Method in class org.deeplearning4j.nn.HiddenLayer
-
- getnOut() - Method in class org.deeplearning4j.nn.LogisticRegression
-
- getnOuts() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getnOuts() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getNumDataSets() - Method in class org.deeplearning4j.test.TestDataSetIterator
-
- getNumNames() - Method in class org.deeplearning4j.base.LFWLoader
-
- getNumParameters() - Method in class org.deeplearning4j.optimize.LogisticRegressionOptimizer
-
- getNumParameters() - Method in class org.deeplearning4j.optimize.MultiLayerNetworkOptimizer
-
- getNumParameters() - Method in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- getNumPixelColumns() - Method in class org.deeplearning4j.base.LFWLoader
-
- getnVisible() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getnVisible() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getOptimizable() - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- getOptimizer() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getOptimizer() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getPairIterator() - Method in class org.deeplearning4j.berkeley.CounterMap
-
- getParameter(int) - Method in class org.deeplearning4j.optimize.LogisticRegressionOptimizer
-
- getParameter(int) - Method in class org.deeplearning4j.optimize.MultiLayerNetworkOptimizer
-
- getParameter(int) - Method in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- getParameters(double[]) - Method in class org.deeplearning4j.optimize.LogisticRegressionOptimizer
-
- getParameters(double[]) - Method in class org.deeplearning4j.optimize.MultiLayerNetworkOptimizer
-
- getParameters(double[]) - Method in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- 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.
- getReconstructedInput(DoubleMatrix) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
- getReconstructionCrossEntropy() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getReConstructionCrossEntropy() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
Reconstruction entropy.
- getReConstructionCrossEntropy() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getRenderEpochs() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getRenderEpochs() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getRenderWeightsEveryNEpochs() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getRenderWeightsEveryNEpochs() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getRng() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getRng() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getRng() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getRng() - Method in class org.deeplearning4j.nn.HiddenLayer
-
- getRng() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getRows() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Number of rows per image.
- getSecond() - Method in class org.deeplearning4j.berkeley.Pair
-
- getSecond() - Method in class org.deeplearning4j.berkeley.Triple
-
- getSigmoidLayers() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getSortedKeys() - Method in class org.deeplearning4j.berkeley.Counter
-
- getSparsity() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getSparsity() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getSparsity() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getStepSize() - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- getThird() - Method in class org.deeplearning4j.berkeley.Triple
-
- getValue() - Method in class org.deeplearning4j.optimize.LogisticRegressionOptimizer
-
- getValue() - Method in class org.deeplearning4j.optimize.MultiLayerNetworkOptimizer
-
- getValue() - Method in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- getValueGradient(double[]) - Method in class org.deeplearning4j.optimize.LogisticRegressionOptimizer
-
- getValueGradient(double[]) - Method in class org.deeplearning4j.optimize.MultiLayerNetworkOptimizer
-
- getValueGradient(double[]) - Method in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- getValueGradient(double[]) - Method in class org.deeplearning4j.rbm.RBMOptimizer
-
- getValueGradient(double[]) - Method in class org.deeplearning4j.sda.DenoisingAutoEncoderOptimizer
-
- getvBias() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getvBias() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getvBiasGradient() - Method in class org.deeplearning4j.nn.gradient.NeuralNetworkGradient
-
- getVisibleBiasTransforms() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getW() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- getW() - Method in class org.deeplearning4j.nn.HiddenLayer
-
- getW() - Method in class org.deeplearning4j.nn.LogisticRegression
-
- getW() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- getWeightTransforms() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- getWeightTransforms() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- getwGradient() - Method in class org.deeplearning4j.nn.gradient.LogisticRegressionGradient
-
- getwGradient() - Method in class org.deeplearning4j.nn.gradient.NeuralNetworkGradient
-
- gibbhVh(DoubleMatrix) - Method in class org.deeplearning4j.rbm.RBM
-
Gibbs sampling step: hidden ---> visible ---> hidden
- gr(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
Tests if a is greater than b.
- grow(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- gunzipFile(File, File) - Static method in class org.deeplearning4j.base.LFWLoader
-
- gunzipFile(File, File) - Static method in class org.deeplearning4j.base.MnistFetcher
-
- 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
-
- ImageLoader() - Constructor for class org.deeplearning4j.util.ImageLoader
-
- 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() - Method in class org.deeplearning4j.eval.Evaluation
-
- incrementFalsePositives(int) - Method in class org.deeplearning4j.eval.Evaluation
-
- incrementTruePositives() - Method in class org.deeplearning4j.eval.Evaluation
-
- information(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the entropy for a given vector of probabilities.
- init() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- initCentroids() - Method in class org.deeplearning4j.clustering.KMeansClustering
-
Init clusters using the k-means++ algorithm.
- initializeCurrFromList(List<Pair<DoubleMatrix, DoubleMatrix>>) - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- initializeLayers(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Base class for initializing the layers based on the input.
- initializeNetwork(NeuralNetwork) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- initIfPossible(DoubleMatrix) - Method in class org.deeplearning4j.clustering.KMeansClustering
-
- initWeights() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
Initialize weights.
- input - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- 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
-
- inputColumns() - Method in interface org.deeplearning4j.datasets.iterator.DataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.test.TestDataSetIterator
-
- InputSplit - Class in org.deeplearning4j.util
-
- InputSplit() - Constructor for class org.deeplearning4j.util.InputSplit
-
- inputStreamFromPath(String) - Static method in class org.deeplearning4j.util.DeepLearningIOUtil
-
- 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
-
- 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.
- 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
- 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
-
- IrisUtils - Class in org.deeplearning4j.base
-
- IrisUtils() - Constructor for class org.deeplearning4j.base.IrisUtils
-
- isConverged() - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- 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).
- isEqualTo(Counter<E>) - Method in class org.deeplearning4j.berkeley.Counter
-
- isEqualTo(CounterMap<K, V>) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- isForceNumEpochs() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- isForceNumEpochs() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- isGreater(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- isInfinite(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- isNaN(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- isReady() - Method in class org.deeplearning4j.clustering.KMeansClustering
-
- isShouldBackProp() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- isShouldBackProp() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- isShouldInit() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- isShouldInit() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- isToDecode() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- isToDecode() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- isUseRegularization() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- isUseRegularization() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- isUseRegularization() - Method in class org.deeplearning4j.nn.LogisticRegression
-
- isValidOutcome(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- 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.
- iterator(int) - Method in class org.deeplearning4j.datasets.DataSet
-
- iterator() - Method in class org.deeplearning4j.datasets.DataSet
-
- 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.FilteredIterator(Filter<T>, Iterator<T>) - Constructor for class org.deeplearning4j.berkeley.Iterators.FilteredIterator
-
- Iterators.FilteredIterator(Filter<T>, Iterable<T>) - Constructor for class org.deeplearning4j.berkeley.Iterators.FilteredIterator
-
- Iterators.IteratorIterator<T> - Class in org.deeplearning4j.berkeley
-
Wraps a two-level iteration scenario in an iterator.
- Iterators.IteratorIterator(Iterator, Factory<Iterator<T>>) - Constructor for class org.deeplearning4j.berkeley.Iterators.IteratorIterator
-
- Iterators.Transform<S,T> - Class in org.deeplearning4j.berkeley
-
Wraps a base iterator with a transformation function.
- Iterators.Transform(Iterator<S>) - Constructor for class org.deeplearning4j.berkeley.Iterators.Transform
-
- Iterators.TransformingIterator<I,O> - Class in org.deeplearning4j.berkeley
-
- Iterators.TransformingIterator(Iterator<I>, MyMethod<I, O>) - Constructor for class org.deeplearning4j.berkeley.Iterators.TransformingIterator
-
- l2 - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- l2 - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- l2RegularizedCoefficient() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- l2RegularizedCoefficient() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- lambert(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- layers - Variable in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- learningRateUpdate - Variable in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- leftChild(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- 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() - Constructor for class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
-
- LFWDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
- LFWDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
- LFWLoader - Class in org.deeplearning4j.base
-
- LFWLoader() - Constructor for class org.deeplearning4j.base.LFWLoader
-
- ListDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
Wraps a data set 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
- load(File) - Static method in class org.deeplearning4j.datasets.DataSet
-
- load(InputStream) - Method in class org.deeplearning4j.datasets.DataSet
-
- load(InputStream) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- load(InputStream) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- load(InputStream) - Method in class org.deeplearning4j.nn.gradient.MultiLayerGradient
-
- load(InputStream) - Method in class org.deeplearning4j.nn.gradient.NeuralNetworkGradient
-
- load(InputStream) - Method in interface org.deeplearning4j.nn.Persistable
-
- LoadAndDraw - Class in org.deeplearning4j.datasets.mnist.draw
-
- LoadAndDraw() - Constructor for class org.deeplearning4j.datasets.mnist.draw.LoadAndDraw
-
- loadFromFile(InputStream) - Static method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- loadIris(int, int) - Static method in class org.deeplearning4j.base.IrisUtils
-
- loadIris() - Static method in class org.deeplearning4j.base.IrisUtils
-
- loadIris(int) - Static method in class org.deeplearning4j.base.IrisUtils
-
- log - Static variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- log - Static variable in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- log(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- 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
-
- LogisticRegression - Class in org.deeplearning4j.nn
-
Logistic regression implementation with jblas.
- LogisticRegression(DoubleMatrix, DoubleMatrix, int, int) - Constructor for class org.deeplearning4j.nn.LogisticRegression
-
- LogisticRegression(DoubleMatrix, int, int) - Constructor for class org.deeplearning4j.nn.LogisticRegression
-
- LogisticRegression(int, int) - Constructor for class org.deeplearning4j.nn.LogisticRegression
-
- LogisticRegression.Builder - Class in org.deeplearning4j.nn
-
- LogisticRegression.Builder() - Constructor for class org.deeplearning4j.nn.LogisticRegression.Builder
-
- LogisticRegressionGradient - Class in org.deeplearning4j.nn.gradient
-
- LogisticRegressionGradient(DoubleMatrix, DoubleMatrix) - Constructor for class org.deeplearning4j.nn.gradient.LogisticRegressionGradient
-
- LogisticRegressionOptimizer - Class in org.deeplearning4j.optimize
-
- LogisticRegressionOptimizer(LogisticRegression, double) - Constructor for class org.deeplearning4j.optimize.LogisticRegressionOptimizer
-
- logLayer - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- 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).
- LogTransform - Class in org.deeplearning4j.transformation
-
- LogTransform() - Constructor for class org.deeplearning4j.transformation.LogTransform
-
- 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(Object[]) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
- lossFunction(Object[]) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
The loss function (cross entropy, reconstruction error,...)
- lossFunction() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- lossFunction(Object[]) - Method in class org.deeplearning4j.rbm.RBM
-
- lr - Variable in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- magnitude(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- 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 functions provided
in this module.
- main(String[]) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- main(String[]) - Static method in class org.deeplearning4j.datasets.DataSet
-
- main(String[]) - Static method in class org.deeplearning4j.datasets.mnist.draw.LoadAndDraw
-
- main(String[]) - Static method in class org.deeplearning4j.eval.ConfusionMatrix
-
- main(String[]) - Static method in class org.deeplearning4j.eval.DataSetTester
-
- main(String[]) - Static method in class org.deeplearning4j.eval.ModelTester
-
- main(String[]) - Static method in class org.deeplearning4j.util.MathUtils
-
- makePair(S, T) - Static method in class org.deeplearning4j.berkeley.Pair
-
- makeTriple(S, T, U) - Static method in class org.deeplearning4j.berkeley.Triple
-
- ManhattanDistance - Class in org.deeplearning4j.distancefunction
-
- ManhattanDistance(DoubleMatrix) - Constructor for class org.deeplearning4j.distancefunction.ManhattanDistance
-
- manhattanDistance(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This will calculate the Manhattan distance between two sets of points.
- 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.HashMapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory.HashMapFactory
-
- MapFactory.IdentityHashMapFactory<K,V> - Class in org.deeplearning4j.berkeley
-
- MapFactory.IdentityHashMapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory.IdentityHashMapFactory
-
- MapFactory.TreeMapFactory<K,V> - Class in org.deeplearning4j.berkeley
-
- MapFactory.TreeMapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory.TreeMapFactory
-
- MapFactory.WeakHashMapFactory<K,V> - Class in org.deeplearning4j.berkeley
-
- MapFactory.WeakHashMapFactory() - Constructor for class org.deeplearning4j.berkeley.MapFactory.WeakHashMapFactory
-
- 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
-
- MatrixTransform - Interface in org.deeplearning4j.transformation
-
- MatrixUtil - Class in org.deeplearning4j.util
-
- MatrixUtil() - Constructor for class org.deeplearning4j.util.MatrixUtil
-
- 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
-
- max(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- maxIndex(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Returns index of maximum element in a given
array of doubles.
- maxIndex(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- maxLengthIterator(Iterator<T>, int) - Static method in class org.deeplearning4j.berkeley.Iterators
-
Provides a max number of elements for an underlying base iterator.
- mean(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
Computes the mean for an array of doubles.
- mean(DoubleMatrix, int) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- meanSquaredError(DoubleMatrix, DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
Returns the mean squared error of the 2 matrices.
- merge(List<DataSet>) - Static method in class org.deeplearning4j.datasets.DataSet
-
- merge(BaseMultiLayerNetwork, int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Merges this network with the other one.
- merge(NeuralNetwork, int) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- merge(LogisticRegression, int) - Method in class org.deeplearning4j.nn.LogisticRegression
-
Averages the given logistic regression
from a mini batch in to this one
- merge(NeuralNetwork, int) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
Performs a network merge in the form of
a += b - a / n
where a is a matrix here
b is a matrix on the incoming network
and n is the batch size
- 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
-
- min(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- minLearningRate - Variable in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- 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() - Constructor for class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- MnistDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
- MnistDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator
-
- 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.
- ModelTester - Class in org.deeplearning4j.eval
-
- ModelTester() - Constructor for class org.deeplearning4j.eval.ModelTester
-
- momentum - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- momentum - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- MultiLayerGradient - Class in org.deeplearning4j.nn.gradient
-
Gradient for a whole multi layer network
- MultiLayerGradient(List<NeuralNetworkGradient>, LogisticRegressionGradient) - Constructor for class org.deeplearning4j.nn.gradient.MultiLayerGradient
-
- MultiLayerNetworkOptimizer - Class in org.deeplearning4j.optimize
-
Optimizes the logistic layer for finetuning
a multi layer network.
- MultiLayerNetworkOptimizer(BaseMultiLayerNetwork, double) - Constructor for class org.deeplearning4j.optimize.MultiLayerNetworkOptimizer
-
- Multiply - Class in org.deeplearning4j.transformation
-
- Multiply() - Constructor for class org.deeplearning4j.transformation.Multiply
-
- MultiplyScalar - Class in org.deeplearning4j.transformation
-
- MultiplyScalar(double) - Constructor for class org.deeplearning4j.transformation.MultiplyScalar
-
- MyMethod<I,O> - Interface in org.deeplearning4j.berkeley
-
A function wrapping interface.
- nChooseK(int, int) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
Computes n choose k in an efficient way.
- nearestCentroid(DoubleMatrix) - Method in class org.deeplearning4j.clustering.KMeansClustering
-
- negativeLoglikelihood(double) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
Negative log likelihood of the current input given
the corruption level
- negativeLogLikelihood() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Negative log likelihood of the model
- negativeLogLikelihood() - Method in class org.deeplearning4j.nn.LogisticRegression
-
Objective function: minimize negative log likelihood
- network - Variable in class org.deeplearning4j.optimize.MultiLayerNetworkOptimizer
-
- network - Variable in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- NeuralNetConfiguration - Class in org.deeplearning4j.conf
-
- NeuralNetConfiguration() - Constructor for class org.deeplearning4j.conf.NeuralNetConfiguration
-
- NeuralNetEpochListener - Interface in org.deeplearning4j.optimize
-
- 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
-
- NeuralNetwork - Interface in org.deeplearning4j.nn
-
- NeuralNetworkGradient - Class in org.deeplearning4j.nn.gradient
-
Represents the gradient for changing a neural network
- NeuralNetworkGradient(DoubleMatrix, DoubleMatrix, DoubleMatrix) - Constructor for class org.deeplearning4j.nn.gradient.NeuralNetworkGradient
-
- NeuralNetworkOptimizer - Class in org.deeplearning4j.optimize
-
Performs basic beam search based on the network's loss function
- NeuralNetworkOptimizer(BaseNeuralNetwork, double, Object[]) - Constructor for class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- newInstance(Object...) - Method in class org.deeplearning4j.berkeley.Factory.DefaultFactory
-
- newInstance(Object...) - Method in interface org.deeplearning4j.berkeley.Factory
-
- 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
-
- 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() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- next() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- next() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
- next() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Move to the next entry.
- next() - Method in class org.deeplearning4j.test.TestDataSetIterator
-
- nextBoolean() - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- nextBytes(byte[]) - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- nextDouble() - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- nextFloat() - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- nextGaussian() - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- nextImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Move the cursor to the next image.
- nextInt() - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- nextInt(int) - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- nextList(List<Iterator<T>>) - Static method in class org.deeplearning4j.berkeley.Iterators
-
- nextLong() - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- nHidden - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
-
Number of hidden units
One tip with this is usually having
more hidden units than inputs (read: input rows here)
will typically cause terrible overfitting.
- nIn(int) - Method in class org.deeplearning4j.nn.HiddenLayer.Builder
-
- nIns - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- nLayers - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- noNaNDivide(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
-
- NonZeroStoppingConjugateGradient - Class in org.deeplearning4j.util
-
Modified based on cc.mallet.optimize.ConjugateGradient
no termination when zero tolerance
- NonZeroStoppingConjugateGradient(Optimizable.ByGradientValue, double) - Constructor for class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- NonZeroStoppingConjugateGradient(Optimizable.ByGradientValue, NeuralNetEpochListener) - Constructor for class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- NonZeroStoppingConjugateGradient(Optimizable.ByGradientValue, double, NeuralNetEpochListener) - Constructor for class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- NonZeroStoppingConjugateGradient(Optimizable.ByGradientValue) - Constructor for class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- normalize() - Method in class org.deeplearning4j.berkeley.Counter
-
Destructively normalize this Counter in place.
- normalize() - Method in class org.deeplearning4j.berkeley.CounterMap
-
- 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.
- normalize(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- normalizeByColumnMeans(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
Subtracts by column mean.
- normalizeByColumnSums(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- normalizeByRowSums(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- normalizeMatrix(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- normalizeToOne(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
- normalizeWithDiscount(double) - Method in class org.deeplearning4j.berkeley.CounterMap
-
- nOut(int) - Method in class org.deeplearning4j.nn.HiddenLayer.Builder
-
- nOuts - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- 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
-
- numberOfInputs(int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
-
- numberOfInputs(int) - Method in class org.deeplearning4j.nn.LogisticRegression.Builder
-
- numberOfOutPuts(int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
-
- numberOfOutputs(int) - Method in class org.deeplearning4j.nn.LogisticRegression.Builder
-
- numberOfVisible(int) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
-
- numExamples() - Method in class org.deeplearning4j.datasets.DataSet
-
- numExamples - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- numExamples() - Method in interface org.deeplearning4j.datasets.iterator.DataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.test.TestDataSetIterator
-
- numHidden(int) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
-
- numInputs() - Method in class org.deeplearning4j.datasets.DataSet
-
- numOutcomes() - Method in class org.deeplearning4j.datasets.DataSet
-
- numOutcomes - Variable in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
-
- numTimesIterated - Variable in class org.deeplearning4j.rbm.RBMOptimizer
-
- numtimesPredicted(int) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the number of times a given label was predicted
- numTimesPredicted(int, int) - Method in class org.deeplearning4j.eval.Evaluation
-
Gets the number of times the
given class was predicted for the
given predicted label
- nVisible - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- 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.
- 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.
- 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.DefaultLexicographicPairComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.DefaultLexicographicPairComparator
-
- Pair.FirstComparator<S extends Comparable<? super S>,T> - Class in org.deeplearning4j.berkeley
-
- Pair.FirstComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.FirstComparator
-
- Pair.LexicographicPairComparator<F,S> - Class in org.deeplearning4j.berkeley
-
- Pair.LexicographicPairComparator(Comparator<F>, Comparator<S>) - Constructor for class org.deeplearning4j.berkeley.Pair.LexicographicPairComparator
-
- Pair.ReverseFirstComparator<S extends Comparable<? super S>,T> - Class in org.deeplearning4j.berkeley
-
- Pair.ReverseFirstComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.ReverseFirstComparator
-
- Pair.ReverseSecondComparator<S,T extends Comparable<? super T>> - Class in org.deeplearning4j.berkeley
-
- Pair.ReverseSecondComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.ReverseSecondComparator
-
- Pair.SecondComparator<S,T extends Comparable<? super T>> - Class in org.deeplearning4j.berkeley
-
- Pair.SecondComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.SecondComparator
-
- parent(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- 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 set 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.
- 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.
- Persistable - Interface in org.deeplearning4j.nn
-
- plotActivations(NeuralNetwork) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- plotMatrices(String[], DoubleMatrix[]) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- plotNetworkGradient(NeuralNetwork, NeuralNetworkGradient) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- plotWeights(NeuralNetwork) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- PowScale - Class in org.deeplearning4j.transformation
-
- PowScale(double) - Constructor for class org.deeplearning4j.transformation.PowScale
-
- precision() - Method in class org.deeplearning4j.eval.Evaluation
-
- precision(int) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the precision for a given label
- predict(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Label the probabilities of the input
- predict(DoubleMatrix) - Method in class org.deeplearning4j.nn.LogisticRegression
-
Classify input
- pretrain(DoubleMatrix, Object[]) - Method in class org.deeplearning4j.dbn.DBN
-
- pretrain(DoubleMatrix, int, double, int) - Method in class org.deeplearning4j.dbn.DBN
-
This unsupervised learning method runs
contrastive divergence on each RBM layer in the network.
- pretrain(int, double, int) - Method in class org.deeplearning4j.dbn.DBN
-
- pretrain(DoubleMatrix, Object[]) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Pretrain the network with the given parameters
- pretrain(double, double, int) - Method in class org.deeplearning4j.sda.StackedDenoisingAutoEncoder
-
- pretrain(DoubleMatrix, Object[]) - Method in class org.deeplearning4j.sda.StackedDenoisingAutoEncoder
-
- pretrain(DoubleMatrix, double, double, int) - Method in class org.deeplearning4j.sda.StackedDenoisingAutoEncoder
-
Unsupervised pretraining based on reconstructing the input
from a corrupted version
- 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.
- printStringOneCharPerLine(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- 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(DoubleMatrix) - Method in class org.deeplearning4j.rbm.CRBM
-
- propDown(DoubleMatrix) - Method in class org.deeplearning4j.rbm.RBM
-
Propagates hidden down to visible
- propUp(DoubleMatrix) - Method in class org.deeplearning4j.rbm.RBM
-
- 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.
- randomDoubleBetween(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
- randomNumberBetween(double, double) - Static method in class org.deeplearning4j.util.MathUtils
-
- RBM - Class in org.deeplearning4j.rbm
-
Restricted Boltzmann Machine.
- RBM() - Constructor for class org.deeplearning4j.rbm.RBM
-
- RBM(DoubleMatrix, int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, double, RealDistribution) - Constructor for class org.deeplearning4j.rbm.RBM
-
- RBM.Builder - Class in org.deeplearning4j.rbm
-
- RBM.Builder() - Constructor for class org.deeplearning4j.rbm.RBM.Builder
-
- RBMOptimizer - Class in org.deeplearning4j.rbm
-
- RBMOptimizer(BaseNeuralNetwork, double, Object[]) - Constructor for class org.deeplearning4j.rbm.RBMOptimizer
-
- 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.
- 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
-
- recall() - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the recall for the outcomes
- reconstruct(DoubleMatrix) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
- reconstruct(DoubleMatrix, int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Reconstructs the input.
- reconstruct(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- reconstruct(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
All neural networks are based on this idea of
minimizing reconstruction error.
- reconstruct(DoubleMatrix) - Method in class org.deeplearning4j.rbm.RBM
-
Reconstructs the visible input.
- 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.iterator.BaseDatasetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- remove() - Method in class org.deeplearning4j.test.TestDataSetIterator
-
- 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
-
- renderActivations(int, int, DoubleMatrix, String, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
- renderAllHistograms(NeuralNetwork) - Method in class org.deeplearning4j.plot.FilterRenderer
-
Figure 2.
- renderFilter(DoubleMatrix, int, int, long) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
-
- renderFilters(DoubleMatrix, String, int, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
Once the probability image and weight histograms are
behaving satisfactorily, we plot the learned filter
for each hidden neuron, one per column of W.
- renderHiddenBiases(int, int, DoubleMatrix, String) - Method in class org.deeplearning4j.plot.FilterRenderer
-
- renderHistogram(DoubleMatrix, String, int) - Method in class org.deeplearning4j.plot.FilterRenderer
-
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.
- renderWeights(int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
-
Whether to plot weights or not
- renderWeights(int) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
-
- renderWeightsEveryNEpochs - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- renderWeightsEveryNumEpochs - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- reset() - Method in class org.deeplearning4j.clustering.KMeansClustering
-
- 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
-
- reset() - Method in interface org.deeplearning4j.datasets.iterator.DataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- reset() - Method in class org.deeplearning4j.test.TestDataSetIterator
-
- reset() - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- reverse() - Method in class org.deeplearning4j.berkeley.Pair
-
- rightChild(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- rng - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- rng - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- 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
-
- 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.
- roundToTheNearest(int) - Method in class org.deeplearning4j.datasets.DataSet
-
- roundToTheNearest(DoubleMatrix, double) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- run() - Method in class org.deeplearning4j.eval.DataSetTester
-
- 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
- sample(int) - Method in class org.deeplearning4j.datasets.DataSet
-
Sample without replacement and a random rng
- sample(int, RandomGenerator) - Method in class org.deeplearning4j.datasets.DataSet
-
Sample without replacement
- sample(int, boolean) - Method in class org.deeplearning4j.datasets.DataSet
-
Sample a dataset numSamples times
- sample(int, RandomGenerator, boolean) - Method in class org.deeplearning4j.datasets.DataSet
-
Sample a dataset
- sample_h_given_v() - Method in class org.deeplearning4j.nn.HiddenLayer
-
Sample this hidden layer given the last input.
- sampleDoublesInInterval(double[][], int) - Static method in class org.deeplearning4j.util.MathUtils
-
- sampleHGivenV(DoubleMatrix) - Method in class org.deeplearning4j.nn.HiddenLayer
-
Sample this hidden layer given the input
and initialize this layer with the given input
- sampleHiddenGivenVisible(DoubleMatrix) - Method in class org.deeplearning4j.rbm.RBM
-
Binomial sampling of the hidden values given visible
- sampleVGivenH(DoubleMatrix) - Method in class org.deeplearning4j.rbm.CRBM
-
- sampleVGivenH(DoubleMatrix) - Method in class org.deeplearning4j.rbm.RBM
-
Guess the visible values given the hidden
- saveImageToDisk(BufferedImage, String) - Static method in class org.deeplearning4j.plot.FilterRenderer
-
- saveObject(Object, File) - Static method in class org.deeplearning4j.util.SerializationUtils
-
- saveTo(File, boolean) - Method in class org.deeplearning4j.datasets.DataSet
-
- saveToDisk(String) - Method in class org.deeplearning4j.plot.FilterRenderer
-
- ScalarMatrixTransform - Class in org.deeplearning4j.transformation
-
- ScalarMatrixTransform(double) - Constructor for class org.deeplearning4j.transformation.ScalarMatrixTransform
-
- 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
- scaleBy - Variable in class org.deeplearning4j.transformation.ScalarMatrixTransform
-
- scaledClone(double) - Method in class org.deeplearning4j.berkeley.Counter
-
- SerializationUtils - Class in org.deeplearning4j.util
-
- SerializationUtils() - Constructor for class org.deeplearning4j.util.SerializationUtils
-
- setActivation(ActivationFunction) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setActivation(ActivationFunction) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setActivationFunction(ActivationFunction) - Method in class org.deeplearning4j.nn.HiddenLayer
-
- setAllCounts(double) - Method in class org.deeplearning4j.berkeley.Counter
-
Sets all counts to the given value, but does not remove any keys
- setB(DoubleMatrix) - Method in class org.deeplearning4j.nn.HiddenLayer
-
- setB(DoubleMatrix) - Method in class org.deeplearning4j.nn.LogisticRegression
-
- setbGradient(DoubleMatrix) - Method in class org.deeplearning4j.nn.gradient.LogisticRegressionGradient
-
- setColumnMeans(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setColumnStds(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setColumnSums(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- 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
-
- 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.
- 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
-
- setDist(RealDistribution) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setDist(RealDistribution) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setDist(RealDistribution) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setDist(RealDistribution) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setErrorTolerance(double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setEvaluator(OptimizerEvaluator.ByGradient) - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- setFanIn(double) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setFanIn(double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setFanIn(double) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setFanIn(double) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setFirst(F) - Method in class org.deeplearning4j.berkeley.Pair
-
- setFirst(S) - Method in class org.deeplearning4j.berkeley.Triple
-
- setForceNumEpochs(boolean) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setForceNumEpochs(boolean) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setGradients(List<NeuralNetworkGradient>) - Method in class org.deeplearning4j.nn.gradient.MultiLayerGradient
-
- sethBias(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- sethBias(DoubleMatrix) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- sethBiasGradient(DoubleMatrix) - Method in class org.deeplearning4j.nn.gradient.NeuralNetworkGradient
-
- setHiddenLayerSizes(int[]) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setHiddenLayerSizes(int[]) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setInitialStepSize(double) - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- setInput(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Note that if input isn't null
and the layers are null, this is a way
of initializing the neural network
- setInput(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setInput(DoubleMatrix) - Method in class org.deeplearning4j.nn.HiddenLayer
-
- setInput(DoubleMatrix) - Method in class org.deeplearning4j.nn.LogisticRegression
-
- setInput(DoubleMatrix) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setL2(double) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setL2(double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setL2(double) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setL2(double) - Method in class org.deeplearning4j.nn.LogisticRegression
-
- setL2(double) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setLabels(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setLabels(DoubleMatrix) - Method in class org.deeplearning4j.nn.LogisticRegression
-
- setLayers(NeuralNetwork[]) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setLearningRateUpdate(double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setLineMaximizer(LineOptimizer.ByGradient) - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- setLogLayer(LogisticRegression) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setLogLayer(LogisticRegression) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setLogRegGradient(LogisticRegressionGradient) - Method in class org.deeplearning4j.nn.gradient.MultiLayerGradient
-
- 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.
- setMaxIterations(int) - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- 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.conf.NeuralNetConfiguration
-
- setMomentum(double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setMomentum(double) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setMomentum(double) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setnHidden(int) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setnHidden(int) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setnIn(int) - Method in class org.deeplearning4j.nn.HiddenLayer
-
- setnIn(int) - Method in class org.deeplearning4j.nn.LogisticRegression
-
- setnIns(int) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setnIns(int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setnLayers(int) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setnLayers(int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setnOut(int) - Method in class org.deeplearning4j.nn.HiddenLayer
-
- setnOut(int) - Method in class org.deeplearning4j.nn.LogisticRegression
-
- setnOuts(int) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setnOuts(int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setnVisible(int) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setnVisible(int) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setOptimizer(MultiLayerNetworkOptimizer) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setOptimizer(MultiLayerNetworkOptimizer) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setParameter(int, double) - Method in class org.deeplearning4j.optimize.LogisticRegressionOptimizer
-
- setParameter(int, double) - Method in class org.deeplearning4j.optimize.MultiLayerNetworkOptimizer
-
- setParameter(int, double) - Method in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- setParameters(double[]) - Method in class org.deeplearning4j.optimize.LogisticRegressionOptimizer
-
- setParameters(double[]) - Method in class org.deeplearning4j.optimize.MultiLayerNetworkOptimizer
-
- setParameters(double[]) - Method in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- setRenderEpochs(int) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setRenderEpochs(int) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setRenderWeightsEveryNEpochs(int) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setRenderWeightsEveryNEpochs(int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setRng(RandomGenerator) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setRng(RandomGenerator) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setRng(RandomGenerator) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setRng(RandomGenerator) - Method in class org.deeplearning4j.nn.HiddenLayer
-
- setRng(RandomGenerator) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setSecond(S) - Method in class org.deeplearning4j.berkeley.Pair
-
- setSecond(T) - Method in class org.deeplearning4j.berkeley.Triple
-
- setSeed(int) - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- setSeed(int[]) - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- setSeed(long) - Method in class org.deeplearning4j.rng.SynchronizedRandomGenerator
- setShouldBackProp(boolean) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setShouldBackProp(boolean) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setShouldInit(boolean) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setShouldInit(boolean) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setSigmoidLayers(HiddenLayer[]) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setSparsity(double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setSparsity(double) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setSparsity(double) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setThird(U) - Method in class org.deeplearning4j.berkeley.Triple
-
- setToDecode(boolean) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setToDecode(boolean) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setTolerance(double) - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
-
- setUseRegularization(boolean) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setUseRegularization(boolean) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setUseRegularization(boolean) - Method in class org.deeplearning4j.nn.LogisticRegression
-
- SetUtils - Class in org.deeplearning4j.util
-
- setvBias(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setvBias(DoubleMatrix) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setvBiasGradient(DoubleMatrix) - Method in class org.deeplearning4j.nn.gradient.NeuralNetworkGradient
-
- setW(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- setW(DoubleMatrix) - Method in class org.deeplearning4j.nn.HiddenLayer
-
- setW(DoubleMatrix) - Method in class org.deeplearning4j.nn.LogisticRegression
-
- setW(DoubleMatrix) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- setWeightTransforms(Map<Integer, MatrixTransform>) - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- setWeightTransforms(Map<Integer, MatrixTransform>) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
- setwGradient(DoubleMatrix) - Method in class org.deeplearning4j.nn.gradient.LogisticRegressionGradient
-
- setwGradient(DoubleMatrix) - Method in class org.deeplearning4j.nn.gradient.NeuralNetworkGradient
-
- shouldBackProp - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- shouldForceEpochs - Variable in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
-
- shouldInit - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- shuffle() - Method in class org.deeplearning4j.datasets.DataSet
-
- Sigmoid - Class in org.deeplearning4j.nn.activation
-
- Sigmoid() - Constructor for class org.deeplearning4j.nn.activation.Sigmoid
-
- sigmoid(double) - Static method in class org.deeplearning4j.util.MathUtils
-
1 / 1 + exp(-x)
- sigmoid(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- 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.
- 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.
- softmax(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- sortAndBatchByNumLabels() - Method in class org.deeplearning4j.datasets.DataSet
-
Sorts the dataset by label:
Splits the data set such that examples are sorted by their labels.
- sortByLabel() - Method in class org.deeplearning4j.datasets.DataSet
-
Organizes the dataset to minimize sampling error
while still allowing efficient batching.
- sparsity - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- 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.
- splitInputs(DoubleMatrix, DoubleMatrix, List<Pair<DoubleMatrix, DoubleMatrix>>, List<Pair<DoubleMatrix, DoubleMatrix>>, double) - Static method in class org.deeplearning4j.util.InputSplit
-
- splitInputs(List<Pair<DoubleMatrix, DoubleMatrix>>, List<Pair<DoubleMatrix, DoubleMatrix>>, List<Pair<DoubleMatrix, DoubleMatrix>>, double) - Static method in class org.deeplearning4j.util.InputSplit
-
- 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.
- splitTestAndTrain(int) - Method in class org.deeplearning4j.datasets.DataSet
-
- SqrtScalar - Class in org.deeplearning4j.transformation
-
- SqrtScalar() - Constructor for class org.deeplearning4j.transformation.SqrtScalar
-
- squaredLoss() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- squaredLoss() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- 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
- StackedDenoisingAutoEncoder - Class in org.deeplearning4j.sda
-
A JBlas implementation of
stacked denoising auto encoders.
- StackedDenoisingAutoEncoder() - Constructor for class org.deeplearning4j.sda.StackedDenoisingAutoEncoder
-
- StackedDenoisingAutoEncoder(int, int[], int, int, RandomGenerator, DoubleMatrix, DoubleMatrix) - Constructor for class org.deeplearning4j.sda.StackedDenoisingAutoEncoder
-
- StackedDenoisingAutoEncoder(int, int[], int, int, RandomGenerator) - Constructor for class org.deeplearning4j.sda.StackedDenoisingAutoEncoder
-
- StackedDenoisingAutoEncoder.Builder - Class in org.deeplearning4j.sda
-
- StackedDenoisingAutoEncoder.Builder() - Constructor for class org.deeplearning4j.sda.StackedDenoisingAutoEncoder.Builder
-
- start() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawMnistGreyScale
-
- start() - Method in class org.deeplearning4j.plot.FilterRenderer
-
- stats() - Method in class org.deeplearning4j.eval.Evaluation
-
- 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.
- StringUtils - Class in org.deeplearning4j.berkeley
-
StringUtils is a class for random String things.
- stripNonAlphaNumerics(String) - Static method in class org.deeplearning4j.berkeley.StringUtils
-
- Subtract - Class in org.deeplearning4j.transformation
-
- Subtract() - Constructor for class org.deeplearning4j.transformation.Subtract
-
- SubtractScalar - Class in org.deeplearning4j.transformation
-
- SubtractScalar(double) - Constructor for class org.deeplearning4j.transformation.SubtractScalar
-
- sum(double[]) - Static method in class org.deeplearning4j.util.MathUtils
-
This returns the sum of the given array.
- sum(DoubleMatrix, int) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- 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.
- sumSquaredError(DoubleMatrix, DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
-
Returns the sum squared error of the 2 matrices.
- swap(int, int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
-
- SynchronizedRandomGenerator - Class in org.deeplearning4j.rng
-
Any RandomGenerator implementation can be thread-safe if it
is used through an instance of this class.
- SynchronizedRandomGenerator(RandomGenerator) - Constructor for class org.deeplearning4j.rng.SynchronizedRandomGenerator
-
Creates a synchronized wrapper for the given RandomGenerator
instance.
- Tanh - Class in org.deeplearning4j.nn.activation
-
- Tanh() - Constructor for class org.deeplearning4j.nn.activation.Tanh
-
- TestDataSetIterator - Class in org.deeplearning4j.test
-
Track number of times the dataset iterator has been called
- TestDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.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
- 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.
- title - Variable in class org.deeplearning4j.datasets.mnist.draw.DrawMnistGreyScale
-
- title - Variable in class org.deeplearning4j.plot.FilterRenderer
-
- 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
- toDecode - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
-
- toDouble(int[][]) - Static method in class org.deeplearning4j.util.ArrayUtil
-
- toHTML() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Outputs Confusion Matrix in an HTML table.
- tolerance - Variable in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- toLogSpace() - Method in class org.deeplearning4j.berkeley.Counter
-
- toMatrix(int[][]) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- toMatrix(int[]) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- toOutcomeArray(int, int) - Static method in class org.deeplearning4j.util.ArrayUtil
-
- toOutcomeVector(int, int) - Static method in class org.deeplearning4j.util.MatrixUtil
-
- 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.datasets.DataSet
-
- toString() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
- 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 - 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
-
- totalExamples() - Method in interface org.deeplearning4j.datasets.iterator.DataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.test.TestDataSetIterator
-
- 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
-
- totalOutcomes() - Method in interface org.deeplearning4j.datasets.iterator.DataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.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).
- train(DoubleMatrix, DoubleMatrix, double) - Method in class org.deeplearning4j.autoencoder.DeepAutoEncoder
-
- train(DoubleMatrix, double, double) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
Perform one iteration of training
- train(DoubleMatrix, double, Object[]) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
- train(DoubleMatrix, double, Object[]) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
Train one iteration of the network
- train(double) - Method in class org.deeplearning4j.nn.LogisticRegression
-
Train with current input and labels
with the given learning rate
- train(DoubleMatrix, double) - Method in class org.deeplearning4j.nn.LogisticRegression
-
Train with the given input
and the currently set labels
- train(DoubleMatrix, DoubleMatrix, double) - Method in class org.deeplearning4j.nn.LogisticRegression
-
Train on the given inputs and labels.
- train(DoubleMatrix, double, Object[]) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- train(DoubleMatrix) - Method in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
-
- train(DoubleMatrix, double, Object[]) - Method in class org.deeplearning4j.rbm.RBM
-
- trainingFileLabelsFilename_unzipped - Static variable in class org.deeplearning4j.base.MnistFetcher
-
- trainingFilesFilename_unzipped - Static variable in class org.deeplearning4j.base.MnistFetcher
-
- trainNetwork(DoubleMatrix, DoubleMatrix, Object[]) - Method in class org.deeplearning4j.dbn.DBN
-
- trainNetwork(DoubleMatrix, DoubleMatrix, Object[]) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
-
Train the network running some unsupervised
pretraining followed by SGD/finetune
- trainNetwork(DoubleMatrix, DoubleMatrix, Object[]) - Method in class org.deeplearning4j.sda.StackedDenoisingAutoEncoder
-
- trainTillConvergence(DoubleMatrix, double, double) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
Run a network optimizer
- trainTillConvergence(DoubleMatrix, double, Object[]) - Method in class org.deeplearning4j.da.DenoisingAutoEncoder
-
- trainTillConvergence(DoubleMatrix, DoubleMatrix, double, int) - Method in class org.deeplearning4j.nn.LogisticRegression
-
Run conjugate gradient with the given x and y
- trainTillConvergence(double, int) - Method in class org.deeplearning4j.nn.LogisticRegression
-
Run conjugate gradient
- trainTillConvergence(DoubleMatrix, double, Object[]) - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- trainTillConvergence(double, int, DoubleMatrix) - Method in class org.deeplearning4j.rbm.RBM
-
Trains till global minimum is found.
- trainTillConvergence(DoubleMatrix, double, Object[]) - Method in class org.deeplearning4j.rbm.RBM
-
Note: k is the first input in params.
- transform(S) - Method in class org.deeplearning4j.berkeley.Iterators.Transform
-
- transformWeightsAt(int, MatrixTransform) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
-
Transform the weights at the given layer
- transformWeightsAt(Map<Integer, MatrixTransform>) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
-
A map of transformations for transforming
the given layers
- transpose() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
-
- transpose() - Method in class org.deeplearning4j.nn.HiddenLayer
-
- transpose() - Method in interface org.deeplearning4j.nn.NeuralNetwork
-
- 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
-
- 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.