ClusteringStrategy clusteringStrategy
IterationHistory iterationHistory
int currentIteration
ClusterSet clusterSet
List<E> initialPoints
KDTree.KDNode root
int dims
int size
HyperRect rect
double x
double y
double hw
double hh
QuadTree parent
QuadTree northWest
QuadTree northEast
QuadTree southWest
QuadTree southEast
boolean isLeaf
int size
int cumSize
Cell boundary
org.nd4j.linalg.api.ndarray.INDArray buf
org.nd4j.linalg.api.ndarray.INDArray data
org.nd4j.linalg.api.ndarray.INDArray centerOfMass
int[] index
int dimension
org.nd4j.linalg.api.ndarray.INDArray corner
org.nd4j.linalg.api.ndarray.INDArray width
int index
org.nd4j.linalg.api.ndarray.INDArray point
int d
String functionName
boolean invert
int index
double distance
int D
org.nd4j.linalg.api.ndarray.INDArray data
int N
org.nd4j.linalg.api.ndarray.INDArray buf
int size
int cumSize
Cell boundary
org.nd4j.linalg.api.ndarray.INDArray centerOfMass
SpTree parent
int[] index
int nodeCapacity
int numChildren
boolean isLeaf
Set<E> indices
SpTree[] children
String similarityFunction
org.canova.api.records.reader.RecordReader recordReader
org.canova.api.io.WritableConverter converter
int batchSize
int labelIndex
int numPossibleLabels
boolean overshot
Iterator<E> sequenceIter
org.nd4j.linalg.dataset.DataSet last
boolean useCurrent
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
boolean binarize
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
int[] hiddenLayerSizes
List<E> confs
boolean useDropConnect
boolean useGaussNewtonVectorProductBackProp
boolean pretrain
boolean useRBMPropUpAsActivations
double dampingFactor
Map<K,V> processors
Map<K,V> inputPreProcessors
boolean backward
double sparsity
boolean useAdaGrad
double lr
double corruptionLevel
int numIterations
double momentum
double l2
boolean useRegularization
String customLossFunction
Map<K,V> momentumAfter
int resetAdaGradIterations
int numLineSearchIterations
double dropOut
boolean applySparsity
WeightInit weightInit
OptimizationAlgorithm optimizationAlgo
org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction lossFunction
boolean constrainGradientToUnitNorm
Random rng
Distribution dist
StepFunction stepFunction
Layer layer
List<E> variables
int nIn
int nOut
String activationFunction
RBM.VisibleUnit visibleUnit
RBM.HiddenUnit hiddenUnit
int k
int[] weightShape
int[] filterSize
int[] stride
int kernel
int batchSize
boolean minimize
double l1
int[] featureMapSize
ConvolutionLayer.ConvolutionType convolutionType
int numberOfTrials
double probabilityOfSuccess
double mean
double std
double upper
double lower
OutputPreProcessor[] preProcessor
InputPreProcessor[] preProcessors
OutputPreProcessor[] outputPreProcessors
int[] shape
long seed
org.nd4j.linalg.api.ndarray.INDArray input
Map<K,V> params
NeuralNetConfiguration conf
org.nd4j.linalg.api.ndarray.INDArray dropoutMask
ParamInitializer paramInitializer
double score
ConvexOptimizer optimizer
Collection<E> iterationListeners
org.nd4j.linalg.api.ndarray.INDArray labels
NeuralNetConfiguration conf
Map<K,V> params
ParamInitializer paramInitializer
List<E> listeners
int rows
int cols
int[] shape
NeuralNetConfiguration conf
Layer convLayer
ParamInitializer paramInitializer
Map<K,V> params
org.nd4j.linalg.api.ndarray.INDArray currInput
org.nd4j.linalg.api.ndarray.INDArray allInput
org.nd4j.linalg.api.ndarray.INDArray visibleLoss
org.nd4j.linalg.api.ndarray.INDArray hiddenLoss
org.nd4j.linalg.api.ndarray.INDArray cLoss
org.nd4j.linalg.api.ndarray.INDArray bLoss
org.nd4j.linalg.api.ndarray.INDArray y
double currScore
org.nd4j.linalg.api.ndarray.INDArray vector
org.nd4j.linalg.api.ndarray.INDArray prediction
List<E> children
double error
Tree parent
String headWord
String value
String label
String type
int goldLabel
List<E> tokens
List<E> tags
String parse
int begin
int end
org.nd4j.linalg.api.rng.Random rng
org.nd4j.linalg.api.ndarray.INDArray sigma
org.nd4j.linalg.api.ndarray.INDArray hiddenSigma
org.nd4j.linalg.api.ndarray.INDArray iFog
org.nd4j.linalg.api.ndarray.INDArray iFogF
org.nd4j.linalg.api.ndarray.INDArray c
org.nd4j.linalg.api.ndarray.INDArray x
org.nd4j.linalg.api.ndarray.INDArray hIn
org.nd4j.linalg.api.ndarray.INDArray hOut
org.nd4j.linalg.api.ndarray.INDArray u
org.nd4j.linalg.api.ndarray.INDArray u2
org.nd4j.linalg.api.ndarray.INDArray xi
org.nd4j.linalg.api.ndarray.INDArray xs
Layer[] layers
org.nd4j.linalg.api.ndarray.INDArray input
org.nd4j.linalg.api.ndarray.INDArray labels
boolean initCalled
List<E> listeners
NeuralNetConfiguration defaultConfiguration
MultiLayerConfiguration layerWiseConfigurations
org.nd4j.linalg.api.ndarray.INDArray mask
Collection<E> listeners
int printIterations
Model function
StepFunction stepFunction
ConvexOptimizer optimizer
int maxIterations
double stpmax
double relTolx
double absTolx
double ALF
NeuralNetConfiguration conf
org.nd4j.linalg.learning.AdaGrad adaGrad
int iteration
StepFunction stepFunction
Collection<E> iterationListeners
Collection<E> terminationConditions
Model model
BackTrackLineSearch lineMaximizer
double step
int batchSize
double score
double oldScore
double stpMax
Map<K,V> adaGradForVariable
Map<K,V> searchState
int m
boolean converged
double initialStepSize
double tolerance
double gradientTolerance
MultiLayerNetwork network
int maxIterations
org.nd4j.linalg.api.ndarray.INDArray ch
org.nd4j.linalg.api.ndarray.INDArray gradient
org.nd4j.linalg.api.ndarray.INDArray xi
double pi
double decrease
double boost
double score
double eps
double tolerance
double gradientTolerance
int N
double perplexity
double theta
org.nd4j.linalg.api.ndarray.INDArray rows
org.nd4j.linalg.api.ndarray.INDArray cols
org.nd4j.linalg.api.ndarray.INDArray vals
org.nd4j.linalg.api.ndarray.INDArray x
int numDimensions
SpTree tree
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
int iterations
NeuralNetPlotter plotter
int patchesPerRow
boolean renderFirst
File dir
Queue<E> paths
ScheduledExecutorService executorService
AtomicBoolean running
Queue<E> save
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
Copyright © 2015. All Rights Reserved.