Index (deeplearning4j-core 0.0.0.2 API)

A B C D E F G H I J K L M N O P R S T U V W X Y Z

A

able(Iterator<T>) - Static method in class org.deeplearning4j.berkeley.Iterators: Wraps an iterator as an iterable
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 - Class in org.deeplearning4j.transformation
Add() - Constructor for class org.deeplearning4j.transformation.Add
add(DoubleMatrix, DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
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.
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
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.
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

B

backProp(double, int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork: Backpropagation of errors for weights
backProp - Variable in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
backPropStep(Double, BaseMultiLayerNetwork, double, int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork: Do a back prop iteration.
base - Variable in class org.deeplearning4j.distancefunction.BaseDistanceFunction
BaseDataFetcher - Class in org.deeplearning4j.datasets.fetchers
BaseDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
BaseDatasetIterator - Class in org.deeplearning4j.datasets.iterator: Baseline implementation includes control over the data fetcher and some basic getters for metadata
BaseDatasetIterator(int, int, DataSetFetcher) - Constructor for class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
BaseDistanceFunction - Class in org.deeplearning4j.distancefunction: Takes in another matrix
BaseDistanceFunction(DoubleMatrix) - Constructor for class org.deeplearning4j.distancefunction.BaseDistanceFunction
BaseMultiLayerNetwork - Class in org.deeplearning4j.nn: A base class for a multi layer neural network with a logistic output layer and multiple hidden layers.
BaseMultiLayerNetwork() - Constructor for class org.deeplearning4j.nn.BaseMultiLayerNetwork
BaseMultiLayerNetwork(int, int[], int, int, RandomGenerator) - Constructor for class org.deeplearning4j.nn.BaseMultiLayerNetwork
BaseMultiLayerNetwork(int, int[], int, int, RandomGenerator, DoubleMatrix, DoubleMatrix) - Constructor for class org.deeplearning4j.nn.BaseMultiLayerNetwork
BaseMultiLayerNetwork.Builder<E extends BaseMultiLayerNetwork> - Class in org.deeplearning4j.nn
BaseMultiLayerNetwork.Builder() - Constructor for class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
BaseNeuralNetwork - Class in org.deeplearning4j.nn: Baseline class for any Neural Network used as a layer in a deep network such as an DBN
BaseNeuralNetwork() - Constructor for class org.deeplearning4j.nn.BaseNeuralNetwork
BaseNeuralNetwork(int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, double) - Constructor for class org.deeplearning4j.nn.BaseNeuralNetwork
BaseNeuralNetwork(DoubleMatrix, int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, double, RealDistribution) - Constructor for class org.deeplearning4j.nn.BaseNeuralNetwork
BaseNeuralNetwork.Builder<E extends BaseNeuralNetwork> - Class in org.deeplearning4j.nn
BaseNeuralNetwork.Builder() - Constructor for class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
batch - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
batch() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
batch() - Method in interface org.deeplearning4j.datasets.iterator.DataSetIterator
batch() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
batchBy(int) - Method in class org.deeplearning4j.datasets.DataSet
batchByNumLabels() - Method in class org.deeplearning4j.datasets.DataSet
bernoullis(double, double, double) - Static method in class org.deeplearning4j.util.MathUtils: This will return the bernoulli trial for the given event.
binomial(RandomGenerator, int, double) - Static method in class org.deeplearning4j.util.MathUtils: Generates a binomial distributed number using the given rng
binomial(DoubleMatrix, int, RandomGenerator) - Static method in class org.deeplearning4j.util.MatrixUtil: Generate a binomial distribution based on the given rng, a matrix of p values, and a max number.
build() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
build() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
build() - Method in class org.deeplearning4j.nn.HiddenLayer.Builder
build() - Method in class org.deeplearning4j.nn.LogisticRegression.Builder
buildCounter(MapFactory<V, Double>) - Method in class org.deeplearning4j.berkeley.CounterMap
buildEmpty() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
buildEmpty() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory
buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.HashMapFactory
buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.IdentityHashMapFactory
buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.TreeMapFactory
buildMap() - Method in class org.deeplearning4j.berkeley.MapFactory.WeakHashMapFactory
ByteUtil - Class in org.deeplearning4j.util
ByteUtil() - Constructor for class org.deeplearning4j.util.ByteUtil

C

call(I) - Method in interface org.deeplearning4j.berkeley.MyMethod
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
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
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.
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(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

D

DataSet - Class in org.deeplearning4j.datasets: A data set (example/outcome pairs) The outcomes are specifically for neural network encoding such that any labels that are considered true are 1s.
DataSet(Pair<DoubleMatrix, DoubleMatrix>) - Constructor for class org.deeplearning4j.datasets.DataSet
DataSet(DoubleMatrix, DoubleMatrix) - Constructor for class org.deeplearning4j.datasets.DataSet
dataSetBatches(int) - Method in class org.deeplearning4j.datasets.DataSet
DataSetFetcher - Interface in org.deeplearning4j.datasets.iterator
DataSetIterator - Interface in org.deeplearning4j.datasets.iterator
DataSetTester - Class in org.deeplearning4j.eval: DataSet runner main class.
DataSetTester(String, String, Integer) - Constructor for class org.deeplearning4j.eval.DataSetTester
DataSetTester(String, String) - Constructor for class org.deeplearning4j.eval.DataSetTester
DBN - Class in org.deeplearning4j.dbn: Deep Belief Network.
DBN() - Constructor for class org.deeplearning4j.dbn.DBN
DBN(int, int[], int, int, RandomGenerator, DoubleMatrix, DoubleMatrix) - Constructor for class org.deeplearning4j.dbn.DBN
DBN(int, int[], int, int, RandomGenerator) - Constructor for class org.deeplearning4j.dbn.DBN
DBN.Builder - Class in org.deeplearning4j.dbn
DBN.Builder() - Constructor for class org.deeplearning4j.dbn.DBN.Builder
decode(DoubleMatrix) - Method in class org.deeplearning4j.autoencoder.DeepAutoEncoder
decodeNetwork(boolean) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder: Whether the network is a decoder for an auto encoder
DeepAutoEncoder - Class in org.deeplearning4j.autoencoder
DeepAutoEncoder(BaseMultiLayerNetwork, Object[]) - Constructor for class org.deeplearning4j.autoencoder.DeepAutoEncoder
DeepLearningException - Exception in org.deeplearning4j.exception
DeepLearningException() - Constructor for exception org.deeplearning4j.exception.DeepLearningException
DeepLearningException(String, Throwable, boolean, boolean) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
DeepLearningException(String, Throwable) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
DeepLearningException(String) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
DeepLearningException(Throwable) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
DeepLearningIOUtil - Class in org.deeplearning4j.util
DeepLearningIOUtil() - Constructor for class org.deeplearning4j.util.DeepLearningIOUtil
DeepLearningTest - Class in org.deeplearning4j.base
DeepLearningTest() - Constructor for class org.deeplearning4j.base.DeepLearningTest
DenoisingAutoEncoder - Class in org.deeplearning4j.da: Denoising Autoencoder.
DenoisingAutoEncoder() - Constructor for class org.deeplearning4j.da.DenoisingAutoEncoder
DenoisingAutoEncoder(int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, double) - Constructor for class org.deeplearning4j.da.DenoisingAutoEncoder
DenoisingAutoEncoder(DoubleMatrix, int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, double, RealDistribution) - Constructor for class org.deeplearning4j.da.DenoisingAutoEncoder
DenoisingAutoEncoder.Builder - Class in org.deeplearning4j.da
DenoisingAutoEncoder.Builder() - Constructor for class org.deeplearning4j.da.DenoisingAutoEncoder.Builder
DenoisingAutoEncoderOptimizer - Class in org.deeplearning4j.sda
DenoisingAutoEncoderOptimizer(BaseNeuralNetwork, double, Object[]) - Constructor for class org.deeplearning4j.sda.DenoisingAutoEncoderOptimizer
determinationCoefficient(double[], double[], int) - Static method in class org.deeplearning4j.util.MathUtils: This returns the determination coefficient of two vectors given a length
difference(Counter<E>) - Method in class org.deeplearning4j.berkeley.Counter
difference(Collection<? extends T>, Collection<? extends T>) - Static method in class org.deeplearning4j.util.SetUtils: Return is s1 \ s2
disableBackProp() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder: Disables back propagation
discretize(double, double, double, int) - Static method in class org.deeplearning4j.util.MathUtils: Discretize the given value
discretizeColumns(DoubleMatrix, int) - Static method in class org.deeplearning4j.util.MatrixUtil
dist - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
dist - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
distanceFinderZValue(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This will translate a vector in to an equivalent integer
DistanceFunction - Interface in org.deeplearning4j.distancefunction
distribution(DoubleMatrix) - Method in class org.deeplearning4j.clustering.KMeansClustering
divColumnsByStDeviation(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil: Divides the given matrix's columns by each column's respective standard deviations
Divide - Class in org.deeplearning4j.transformation
Divide() - Constructor for class org.deeplearning4j.transformation.Divide
dot(DoubleMatrix, DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
dotProduct(Counter<E>) - Method in class org.deeplearning4j.berkeley.Counter
downloadAndUntar() - Method in class org.deeplearning4j.base.MnistFetcher
draw() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawMnistGreyScale
DrawMnist - Class in org.deeplearning4j.datasets.mnist.draw
DrawMnist() - Constructor for class org.deeplearning4j.datasets.mnist.draw.DrawMnist
drawMnist(DataSet, DoubleMatrix) - Static method in class org.deeplearning4j.datasets.mnist.draw.DrawMnist
DrawMnistGreyScale - Class in org.deeplearning4j.datasets.mnist.draw
DrawMnistGreyScale(DoubleMatrix, int, int) - Constructor for class org.deeplearning4j.datasets.mnist.draw.DrawMnistGreyScale
DrawMnistGreyScale(DoubleMatrix) - Constructor for class org.deeplearning4j.datasets.mnist.draw.DrawMnistGreyScale

E

empty() - Static method in class org.deeplearning4j.datasets.DataSet
emptyIterator() - Static method in class org.deeplearning4j.berkeley.Iterators
encode(DoubleMatrix) - Method in class org.deeplearning4j.autoencoder.DeepAutoEncoder
encode(BaseMultiLayerNetwork) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork: Transposes this network to turn it in to ad encoder for the given auto encoder networkk
ensureCounter(K) - Method in class org.deeplearning4j.berkeley.CounterMap
ensureValidOutcomeMatrix(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
entropy(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the entropy (information gain, or uncertainty of a random variable).
entrySet() - Method in class org.deeplearning4j.berkeley.Counter
epochDone(int) - Method in interface org.deeplearning4j.optimize.NeuralNetEpochListener
epochDone(int) - Method in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
equals(Object) - Method in class org.deeplearning4j.berkeley.Pair
equals(Object) - Method in class org.deeplearning4j.berkeley.Triple
equals(Object) - Method in class org.deeplearning4j.nn.LogisticRegressionGradient
equals(Object) - Method in class org.deeplearning4j.nn.NeuralNetworkGradient
errorFor(double, double) - Static method in class org.deeplearning4j.util.MathUtils
errors - Variable in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
errorTolerance - Variable in class org.deeplearning4j.nn.BaseMultiLayerNetwork
EuclideanDistance - Class in org.deeplearning4j.distancefunction
EuclideanDistance(DoubleMatrix) - Constructor for class org.deeplearning4j.distancefunction.EuclideanDistance
euclideanDistance(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the euclidean distance of two vectors sum(i=1,n) (q_i - p_i)^2
euclideanDistance(float[], float[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the euclidean distance of two vectors sum(i=1,n) (q_i - p_i)^2
eval(DoubleMatrix, DoubleMatrix) - Method in class org.deeplearning4j.eval.Evaluation: Collects statistics on the real outcomes vs the guesses.
Evaluation - Class in org.deeplearning4j.eval: Evaluation metrics: precision, recall, f1
Evaluation() - Constructor for class org.deeplearning4j.eval.Evaluation
exampleMaxs() - Method in class org.deeplearning4j.datasets.DataSet
exampleMeans() - Method in class org.deeplearning4j.datasets.DataSet
exampleSums() - Method in class org.deeplearning4j.datasets.DataSet
ExpTransform - Class in org.deeplearning4j.transformation
ExpTransform() - Constructor for class org.deeplearning4j.transformation.ExpTransform
extraParams - Variable in class org.deeplearning4j.optimize.NeuralNetworkOptimizer

F

f1() - Method in class org.deeplearning4j.eval.Evaluation
f1(int) - Method in class org.deeplearning4j.eval.Evaluation: Calculate f1 score for a given class
factorial(double) - Static method in class org.deeplearning4j.util.MathUtils: This will return the factorial of the given number n.
Factory<T> - Interface in org.deeplearning4j.berkeley
Factory.DefaultFactory<T> - Class in org.deeplearning4j.berkeley
Factory.DefaultFactory(Class) - Constructor for class org.deeplearning4j.berkeley.Factory.DefaultFactory
fanIn - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
fanIn() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork: Returns the -fanIn to fanIn coefficient used for initializing the weights.
fanIn(double) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
fanIn - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
fanIn() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
fanIn() - Method in interface org.deeplearning4j.nn.NeuralNetwork
feedForward(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork: Compute activations from input to output of the output layer
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.LFWDataFetcher
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
fetch(int) - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
fetcher - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
FileOperations - Class in org.deeplearning4j.util
fillList(Iterator<? extends T>, List<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
fillList(Iterator<? extends T>) - Static method in class org.deeplearning4j.berkeley.Iterators
Filter<T> - Interface in org.deeplearning4j.berkeley: Filters are boolean functions which accept or reject items.
filter(Iterator<T>, Filter<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
finetune(double, int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
finetune(DoubleMatrix, double, int) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork: Run SGD based on the given labels
flatten(int[][]) - Static method in class org.deeplearning4j.util.ArrayUtil
flatten(double[][]) - Static method in class org.deeplearning4j.util.ArrayUtil
flattenedImageFromFile(File) - Method in class org.deeplearning4j.util.ImageLoader
forceEpochs() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder: Forces use of number of epochs for training SGD style rather than conjugate gradient
forceNumEpochs - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
frame - Variable in class org.deeplearning4j.datasets.mnist.draw.DrawMnistGreyScale
fromFile(File) - Method in class org.deeplearning4j.util.ImageLoader
fromImageFile(int, File) - Method in class org.deeplearning4j.base.LFWLoader
fromString(String, String) - Static method in class org.deeplearning4j.util.MathUtils: This will take a given string and separator and convert it to an equivalent double array.

G

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.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.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
getConnections() - Method in class org.deeplearning4j.datasets.NN
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.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.MnistDbFile: The current entry index.
getCurrentState() - Method in class org.deeplearning4j.datasets.NN
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.MnistDbFile: Number of bytes for each entry.
getEntryLength() - Method in class org.deeplearning4j.datasets.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(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
gethBias() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork
gethBias() - Method in interface org.deeplearning4j.nn.NeuralNetwork
gethBiasGradient() - Method in class org.deeplearning4j.nn.NeuralNetworkGradient
getHeaderSize() - Method in class org.deeplearning4j.datasets.MnistDbFile
getHeaderSize() - Method in class org.deeplearning4j.datasets.MnistImageFile
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
getImages(int, File) - Method in class org.deeplearning4j.base.LFWLoader
getImages() - Method in class org.deeplearning4j.datasets.MnistManager: Get the underlying images file as MnistImageFile.
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.MnistManager: Get the underlying labels file as MnistLabelFile.
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
getMagicNumber() - Method in class org.deeplearning4j.datasets.MnistDbFile: MNIST DB files start with unique integer number.
getMagicNumber() - Method in class org.deeplearning4j.datasets.MnistImageFile
getMagicNumber() - Method in class org.deeplearning4j.datasets.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
getNextState() - Method in class org.deeplearning4j.datasets.NN
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
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.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.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
getState() - Method in class org.deeplearning4j.datasets.NN
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.NeuralNetworkGradient
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
getWeights() - Method in class org.deeplearning4j.datasets.NN
getWeightTransforms() - Method in class org.deeplearning4j.conf.NeuralNetConfiguration
getWeightTransforms() - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
getwGradient() - Method in class org.deeplearning4j.nn.LogisticRegressionGradient
getwGradient() - Method in class org.deeplearning4j.nn.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

H

HardTanh - Class in org.deeplearning4j.nn.activation
HardTanh() - Constructor for class org.deeplearning4j.nn.activation.HardTanh
hashCode() - Method in class org.deeplearning4j.berkeley.Pair
hashCode() - Method in class org.deeplearning4j.berkeley.Triple
hashCode() - Method in class org.deeplearning4j.nn.LogisticRegressionGradient
hashCode() - Method in class org.deeplearning4j.nn.NeuralNetworkGradient
hasMore() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
hasMore() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
hasNext() - Method in class org.deeplearning4j.berkeley.Iterators.FilteredIterator
hasNext() - Method in class org.deeplearning4j.berkeley.Iterators.IteratorIterator
hasNext() - Method in class org.deeplearning4j.berkeley.Iterators.Transform
hasNext() - Method in class org.deeplearning4j.berkeley.Iterators.TransformingIterator
hasNext() - Method in class org.deeplearning4j.berkeley.PriorityQueue
hasNext() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface: Returns true if the priority queue is non-empty
hasNext() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
hasNext() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
hBias - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
heapifyDown(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
heapifyUp(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
HiddenLayer - Class in org.deeplearning4j.nn: Vectorized Hidden Layer
HiddenLayer(int, int, DoubleMatrix, DoubleMatrix, RandomGenerator, DoubleMatrix, ActivationFunction) - Constructor for class org.deeplearning4j.nn.HiddenLayer
HiddenLayer(int, int, DoubleMatrix, DoubleMatrix, RandomGenerator, DoubleMatrix) - Constructor for class org.deeplearning4j.nn.HiddenLayer
HiddenLayer.Builder - Class in org.deeplearning4j.nn
HiddenLayer.Builder() - Constructor for class org.deeplearning4j.nn.HiddenLayer.Builder
hiddenLayerSizes - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
hiddenLayerSizes(int[]) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
hypotenuse(double, double) - Static method in class org.deeplearning4j.util.MathUtils: sqrt(a^2 + b^2) without under/overflow.

I

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.datasets.NN
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
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
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
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
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
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
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

J

jostleWeighMatrix() - Method in class org.deeplearning4j.nn.BaseNeuralNetwork

K

k - Variable in class org.deeplearning4j.rbm.RBMOptimizer
keepBottomNKeys(int) - Method in class org.deeplearning4j.berkeley.Counter
keepTopNKeys(int) - Method in class org.deeplearning4j.berkeley.Counter
keySet() - Method in class org.deeplearning4j.berkeley.Counter: The elements in the counter.
keySet() - Method in class org.deeplearning4j.berkeley.CounterMap: Returns the keys that have been inserted into this CounterMap.
KMeansClustering - Class in org.deeplearning4j.clustering: Shamelessly based on: https://github.com/pmerienne/trident-ml/blob/master/src/main/java/com/github/pmerienne/trident/ml/clustering/KMeans.java adapted to jblas double matrices
KMeansClustering(Integer, Class<? extends DistanceFunction>) - Constructor for class org.deeplearning4j.clustering.KMeansClustering
KMeansClustering(Integer) - Constructor for class org.deeplearning4j.clustering.KMeansClustering
kroneckerDelta(double, double) - Static method in class org.deeplearning4j.util.MathUtils: This returns the kronecker delta of two doubles.

L

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
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_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 (using ObjectInputStream
load(InputStream) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork: Load (using ObjectInputStream
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: Load (using ObjectInputStream
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.
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
LogisticRegressionGradient(DoubleMatrix, DoubleMatrix) - Constructor for class org.deeplearning4j.nn.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
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.
LogTransform - Class in org.deeplearning4j.transformation
LogTransform() - Constructor for class org.deeplearning4j.transformation.LogTransform
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

M

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.datasets.DataSet
main(String[]) - Static method in class org.deeplearning4j.datasets.mnist.draw.LoadAndDraw
main(String[]) - Static method in class org.deeplearning4j.datasets.MNISTViewer
main(String[]) - Static method in class org.deeplearning4j.datasets.NN
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
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(double[]) - Static method in class org.deeplearning4j.util.MathUtils
maxIndex(double[]) - Static method in class org.deeplearning4j.util.MathUtils: Returns index of maximum element in a given array of doubles.
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(double[]) - Static method in class org.deeplearning4j.util.MathUtils
minLearningRate - Variable in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
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 database file containing entries that can represent image or label data.
MnistDbFile(String, String) - Constructor for class org.deeplearning4j.datasets.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 database image file.
MnistImageFile(String, String) - Constructor for class org.deeplearning4j.datasets.MnistImageFile: Creates new MNIST database image file ready for reading.
MnistLabelFile - Class in org.deeplearning4j.datasets: MNIST database label file.
MnistLabelFile(String, String) - Constructor for class org.deeplearning4j.datasets.MnistLabelFile: Creates new MNIST database label file ready for reading.
MnistManager - Class in org.deeplearning4j.datasets: Utility class for working with the MNIST database.
MnistManager(String, String) - Constructor for class org.deeplearning4j.datasets.MnistManager: Constructs an instance managing the two given data files.
MNISTViewer - Class in org.deeplearning4j.datasets
MNISTViewer() - Constructor for class org.deeplearning4j.datasets.MNISTViewer
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
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.

N

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
NeuralNetworkGradient(DoubleMatrix, DoubleMatrix, DoubleMatrix) - Constructor for class org.deeplearning4j.nn.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.MnistDbFile: Move to the next entry.
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.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
NN - Class in org.deeplearning4j.datasets
NN(int, int) - Constructor for class org.deeplearning4j.datasets.NN
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
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
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

O

objectIterator(ObjectInputStream) - Static method in class org.deeplearning4j.berkeley.Iterators
oneDiv(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
oneItemIterator(U) - Static method in class org.deeplearning4j.berkeley.Iterators
oneMinus(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
opt - Variable in class org.deeplearning4j.optimize.NeuralNetworkOptimizer
optimize(DoubleMatrix, double, int) - Method in class org.deeplearning4j.optimize.MultiLayerNetworkOptimizer
optimize() - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
optimize(int) - Method in class org.deeplearning4j.util.NonZeroStoppingConjugateGradient
optimizer - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
optimizer - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
optimizer - Variable in class org.deeplearning4j.rbm.RBM
org.deeplearning4j.autoencoder - package org.deeplearning4j.autoencoder
org.deeplearning4j.base - package org.deeplearning4j.base
org.deeplearning4j.berkeley - package org.deeplearning4j.berkeley
org.deeplearning4j.clustering - package org.deeplearning4j.clustering
org.deeplearning4j.conf - package org.deeplearning4j.conf
org.deeplearning4j.da - package org.deeplearning4j.da
org.deeplearning4j.datasets - package org.deeplearning4j.datasets
org.deeplearning4j.datasets.fetchers - package org.deeplearning4j.datasets.fetchers
org.deeplearning4j.datasets.iterator - package org.deeplearning4j.datasets.iterator
org.deeplearning4j.datasets.iterator.impl - package org.deeplearning4j.datasets.iterator.impl
org.deeplearning4j.datasets.mnist.draw - package org.deeplearning4j.datasets.mnist.draw
org.deeplearning4j.dbn - package org.deeplearning4j.dbn
org.deeplearning4j.distancefunction - package org.deeplearning4j.distancefunction
org.deeplearning4j.eval - package org.deeplearning4j.eval
org.deeplearning4j.exception - package org.deeplearning4j.exception
org.deeplearning4j.nn - package org.deeplearning4j.nn
org.deeplearning4j.nn.activation - package org.deeplearning4j.nn.activation
org.deeplearning4j.optimize - package org.deeplearning4j.optimize
org.deeplearning4j.plot - package org.deeplearning4j.plot
org.deeplearning4j.rbm - package org.deeplearning4j.rbm
org.deeplearning4j.rng - package org.deeplearning4j.rng
org.deeplearning4j.sda - package org.deeplearning4j.sda
org.deeplearning4j.transformation - package org.deeplearning4j.transformation
org.deeplearning4j.util - package org.deeplearning4j.util
out(DoubleMatrix, DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
outcome() - Method in class org.deeplearning4j.datasets.DataSet
outcomes(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil

P

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
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.
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, 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(double, double, int) - 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.MnistDbFile: Move to the previous entry.
prevImage() - Method in class org.deeplearning4j.datasets.MnistImageFile: Move the cursor to the previous image.
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.

R

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(int, int, DoubleMatrix, DoubleMatrix, DoubleMatrix, RandomGenerator, double, RealDistribution) - 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.MnistImageFile: Reads the image at the current position.
readImage() - Method in class org.deeplearning4j.datasets.MnistManager: Reads the current image.
readInput() - Method in class org.deeplearning4j.datasets.NN
readLabel() - Method in class org.deeplearning4j.datasets.MnistLabelFile: Reads the integer at the current position.
readLabel() - Method in class org.deeplearning4j.datasets.MnistManager: Reads the current label.
readObject(File) - Static method in class org.deeplearning4j.util.SerializationUtils
readOutput() - Method in class org.deeplearning4j.datasets.NN
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.
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
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
renderFilter(DoubleMatrix, int, int, long) - Method in class org.deeplearning4j.plot.NeuralNetPlotter
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.datasets.NN
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) - 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

S

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
saveObject(Object, File) - Static method in class org.deeplearning4j.util.SerializationUtils
saveTo(File, boolean) - Method in class org.deeplearning4j.datasets.DataSet
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.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.MnistManager: Set the position to be read.
setCurrentIndex(long) - Method in class org.deeplearning4j.datasets.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
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.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(int[], float[]) - Method in class org.deeplearning4j.datasets.NN: Input values into the system via the input nodes
setInput(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork
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
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
setOutput(int[], float[]) - Method in class org.deeplearning4j.datasets.NN
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.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.LogisticRegressionGradient
setwGradient(DoubleMatrix) - Method in class org.deeplearning4j.nn.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
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.
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
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
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
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
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.

T

Tanh - Class in org.deeplearning4j.nn.activation
Tanh() - Constructor for class org.deeplearning4j.nn.activation.Tanh
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
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.datasets.NN
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
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
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
Triple<S,T,U> - Class in org.deeplearning4j.berkeley
Triple(S, T, U) - Constructor for class org.deeplearning4j.berkeley.Triple

U

uniform(Random, double, double) - Static method in class org.deeplearning4j.util.MathUtils: Generate a uniform random number from the given rng
uniform(RandomGenerator, int, int) - Static method in class org.deeplearning4j.util.MatrixUtil
union(Set<? extends T>, Set<? extends T>) - Static method in class org.deeplearning4j.util.SetUtils
unitVec(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
unroll(DoubleMatrix) - Static method in class org.deeplearning4j.util.MatrixUtil
untarFile(File, File) - Method in class org.deeplearning4j.base.LFWLoader
untarFile(File, File) - Method in class org.deeplearning4j.base.MnistFetcher
update(DoubleMatrix) - Method in class org.deeplearning4j.clustering.KMeansClustering
update() - Method in class org.deeplearning4j.datasets.NN
update(BaseMultiLayerNetwork) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork: Assigns the parameters of this model to the ones specified by this network.
update(BaseNeuralNetwork) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork: Copies params from the passed in network to this one
useRegularization - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
useRegularization(boolean) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder: Use l2 reg
useRegularization(boolean) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
useRegularization - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork

V

validate() - Method in class org.deeplearning4j.datasets.DataSet
vBias - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
vectorLength(double[]) - Static method in class org.deeplearning4j.util.MathUtils: Returns the vector length (sqrt(sum(x_i))

W

W - Variable in class org.deeplearning4j.nn.BaseNeuralNetwork
w_0(double[], double[], int) - Static method in class org.deeplearning4j.util.MathUtils
w_1(double[], double[], int) - Static method in class org.deeplearning4j.util.MathUtils
weightsFor(List<Double>) - Static method in class org.deeplearning4j.util.MathUtils: This returns the minimized loss values for a given vector.
weightsFor(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the minimized loss values for a given vector.
weightTransforms - Variable in class org.deeplearning4j.conf.NeuralNetConfiguration
weightTransforms - Variable in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
withActivation(ActivationFunction) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder: Pick an activation function, default is sigmoid
withActivation(ActivationFunction) - Method in class org.deeplearning4j.nn.HiddenLayer.Builder
withBias(DoubleMatrix) - Method in class org.deeplearning4j.nn.HiddenLayer.Builder
withBias(DoubleMatrix) - Method in class org.deeplearning4j.nn.LogisticRegression.Builder
withClazz(Class<? extends BaseMultiLayerNetwork>) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
withClazz(Class<? extends BaseNeuralNetwork>) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
withDist(RealDistribution) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder: Probability distribution for generating weights
withDistribution(RealDistribution) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
withFanIn(Double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
withHBias(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
withInput(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
withInput(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
withInput(DoubleMatrix) - Method in class org.deeplearning4j.nn.HiddenLayer.Builder
withL2(double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder: L2 coefficient
withL2(double) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
withLabels(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
withMomentum(double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder: Specify momentum
withMomentum(double) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
withRandom(RandomGenerator) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
withRng(RandomGenerator) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
withRng(RandomGenerator) - Method in class org.deeplearning4j.nn.HiddenLayer.Builder
withSparsity(double) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork.Builder
withSparsity(double) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
withVisibleBias(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
withWeights(DoubleMatrix) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork.Builder
withWeights(DoubleMatrix) - Method in class org.deeplearning4j.nn.HiddenLayer.Builder
withWeights(DoubleMatrix) - Method in class org.deeplearning4j.nn.LogisticRegression.Builder
write(OutputStream) - Method in class org.deeplearning4j.datasets.DataSet
write(OutputStream) - Method in class org.deeplearning4j.nn.BaseMultiLayerNetwork: Serializes this to the output stream.
write(OutputStream) - Method in class org.deeplearning4j.nn.BaseNeuralNetwork: Write this to an object output stream
write(OutputStream) - Method in interface org.deeplearning4j.nn.Persistable
writeImageToPpm(int[][], String) - Static method in class org.deeplearning4j.datasets.MnistManager: Writes the given image in the given file using the PPM data format.
writeMatrix(DoubleMatrix) - Method in class org.deeplearning4j.plot.NeuralNetPlotter

X

xorData(int) - Static method in class org.deeplearning4j.util.MatrixUtil
xorData(int, int) - Static method in class org.deeplearning4j.util.MatrixUtil
xVals(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the x values of the given vector.

Y

yVals(double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the odd indexed values for the given vector

Z

zip(Iterator<S>, Iterator<T>) - Static method in class org.deeplearning4j.berkeley.Iterators

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