int cursor
int numOutcomes
int inputColumns
org.nd4j.linalg.dataset.DataSet curr
int totalExamples
au.com.bytecode.opencsv.CSV csv
InputStream is
int labelColumn
org.nd4j.linalg.dataset.DataSet all
org.nd4j.linalg.dataset.DataSet data
LFWLoader loader
int batch
int numExamples
DataSetFetcher fetcher
DataSetPreProcessor preProcessor
int numPasses
int batch
DataSetIterator iter
int passes
DataSetPreProcessor preProcessor
DataSetIterator iter
DataSetPreProcessor preProcessor
org.nd4j.linalg.dataset.DataSet sampleFrom
int batchSize
int totalNumberSamples
int numTimesSampled
DataSetPreProcessor preProcessor
int curr
int batch
List<E> list
DataSetPreProcessor preProcessor
org.nd4j.linalg.dataset.DataSet data
int windowRows
int windowColumns
int cursor
DataSetIterator wrapped
int numDataSets
DataSetPreProcessor preProcessor
File image
ImageLoader loader
boolean binarize
boolean normalize
int label
int numLabels
int threshold
boolean useRBMPropUpAsActivations
BaseMultiLayerNetwork encoder
NeuralNetworkOptimizer optimizer
org.nd4j.linalg.api.ndarray.INDArray sigma
org.nd4j.linalg.api.ndarray.INDArray hiddenSigma
int[] hiddenLayerSizes
Layer[] layers
org.nd4j.linalg.api.ndarray.INDArray input
org.nd4j.linalg.api.ndarray.INDArray labels
MultiLayerNetworkOptimizer optimizer
Map<K,V> weightTransforms
Map<K,V> hiddenBiasTransforms
Map<K,V> visibleBiasTransforms
boolean shouldBackProp
boolean forceNumEpochs
boolean initCalled
boolean sampleFromHiddenActivations
NeuralNetConfiguration defaultConfiguration
List<E> layerWiseConfigurations
double learningRateUpdate
NeuralNetwork[] neuralNets
double errorTolerance
boolean lineSearchBackProp
org.nd4j.linalg.api.ndarray.INDArray mask
boolean useDropConnect
double dampingFactor
boolean useGaussNewtonVectorProductBackProp
int wStart
int wEnd
int biasStart
int biasEnd
org.nd4j.linalg.api.ndarray.INDArray W
org.nd4j.linalg.api.ndarray.INDArray hBias
org.nd4j.linalg.api.ndarray.INDArray vBias
org.nd4j.linalg.api.ndarray.INDArray input
org.nd4j.linalg.api.ndarray.INDArray doMask
org.nd4j.linalg.api.ndarray.INDArray wGradient
org.nd4j.linalg.api.ndarray.INDArray vBiasGradient
org.nd4j.linalg.api.ndarray.INDArray hBiasGradient
int lastMiniBatchSize
org.nd4j.linalg.learning.AdaGrad wAdaGrad
org.nd4j.linalg.learning.AdaGrad hBiasAdaGrad
org.nd4j.linalg.learning.AdaGrad vBiasAdaGrad
NeuralNetConfiguration conf
private void readObject(ObjectInputStream in) throws IOException, ClassNotFoundException
IOException
ClassNotFoundException
float sparsity
boolean useAdaGrad
float lr
int k
float corruptionLevel
int numIterations
float momentum
float l2
int pretrainEpochs
int finetuneEpochs
float pretrainLearningRate
float finetuneLearningRate
boolean useRegularization
Map<K,V> momentumAfter
int resetAdaGradIterations
float dropOut
boolean applySparsity
WeightInit weightInit
NeuralNetwork.OptimizationAlgorithm optimizationAlgo
org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction lossFunction
int renderWeightsEveryNumEpochs
boolean concatBiases
boolean constrainGradientToUnitNorm
long seed
int nIn
int nOut
org.nd4j.linalg.api.activation.ActivationFunction activationFunction
RBM.VisibleUnit visibleUnit
RBM.HiddenUnit hiddenUnit
NeuralNetConfiguration.ActivationType activationType
int[] weightShape
int[] filterSize
int numFeatureMaps
int[] featureMapSize
int[] stride
int numInFeatureMaps
List<E> gradients
OutputLayerGradient logRegGradient
org.nd4j.linalg.api.ndarray.INDArray wGradient
org.nd4j.linalg.api.ndarray.INDArray vBiasGradient
org.nd4j.linalg.api.ndarray.INDArray hBiasGradient
org.nd4j.linalg.api.ndarray.INDArray wGradient
org.nd4j.linalg.api.ndarray.INDArray bGradient
org.nd4j.linalg.api.ndarray.INDArray W
org.nd4j.linalg.api.ndarray.INDArray b
org.nd4j.linalg.api.ndarray.INDArray input
NeuralNetConfiguration conf
org.nd4j.linalg.api.ndarray.INDArray dropoutMask
org.nd4j.linalg.api.ndarray.INDArray labels
org.nd4j.linalg.learning.AdaGrad adaGrad
org.nd4j.linalg.learning.AdaGrad biasAdaGrad
org.nd4j.linalg.api.ndarray.INDArray featureMap
BaseMultiLayerNetwork network
double patience
double patienceIncrease
double bestLoss
int validationEpochs
int miniBatchSize
org.nd4j.linalg.dataset.DataSet testSet
double improvementThreshold
BaseMultiLayerNetwork network
int length
double lr
int epochs
int currentIteration
BaseMultiLayerNetwork network
int length
double lr
int epochs
int currentIteration
StochasticHessianFree h
BaseMultiLayerNetwork network
double lr
int currentIteration
NeuralNetwork network
double lr
Object[] extraParams
double tolerance
List<E> errors
NeuralNetwork.OptimizationAlgorithm optimizationAlgorithm
org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction lossFunction
NeuralNetPlotter plotter
double maxStep
int currIteration
int k
int numTimesIterated
BufferedImage image
int maxIter
double realMin
double initialMomentum
double finalMomentum
double minGain
double momentum
int switchMomentumIteration
boolean normalize
boolean usePca
int stopLyingIteration
double tolerance
double learningRate
org.nd4j.linalg.learning.AdaGrad adaGrad
boolean useAdaGrad
double perplexity
org.nd4j.linalg.api.ndarray.INDArray gains
org.nd4j.linalg.api.ndarray.INDArray yIncs
org.nd4j.linalg.api.ndarray.INDArray y
String commandTemplate
org.apache.commons.math3.random.RandomGenerator wrapped
FingerPrintKeyer keyer
String sep
int numColumns
double metaStability
double pCorrect
org.nd4j.linalg.api.ndarray.INDArray possibleLabels
int states
double logPCorrect
double logPIncorrect
double logMetaInstability
double logOfDiangnalTProb
double logStates
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