A B C D E F G H I L M N O P R S T U V

A

ABSTRACT_VALUE - Static variable in class greycat.ml.neuralnet.loss.Losses

AbstractValue - Class in greycat.ml.neuralnet.loss

Created by assaad on 19/05/2017.

AbstractValue() - Constructor for class greycat.ml.neuralnet.loss.AbstractValue

ActionTraverseOrKeep - Class in greycat.ml.actions

ActionTraverseOrKeep(String) - Constructor for class greycat.ml.actions.ActionTraverseOrKeep

activate(Activation, ExMatrix) - Method in class greycat.ml.neuralnet.process.ProcessGraph

Activation - Interface in greycat.ml.neuralnet.activation

Activations - Class in greycat.ml.neuralnet.activation

Activations() - Constructor for class greycat.ml.neuralnet.activation.Activations

AdaDelta - Class in greycat.ml.neuralnet.optimiser

Created by assaad on 17/02/2017.

add(int, int, double) - Method in class greycat.ml.neuralnet.process.ExMatrix

add(ExMatrix, ExMatrix) - Method in class greycat.ml.neuralnet.process.ProcessGraph

addLayer(int, int, int, int, double[]) - Method in class greycat.ml.neuralnet.NeuralNet

appendColumn(double[]) - Method in class greycat.ml.neuralnet.process.ExMatrix

applyLoss(Loss, ExMatrix, ExMatrix, boolean) - Method in class greycat.ml.neuralnet.process.ProcessGraph

ARGMAX - Static variable in class greycat.ml.neuralnet.loss.Losses

AttributeNode - Class in greycat.ml.preprocessing

AttributeNode(long, long, long, Graph) - Constructor for class greycat.ml.preprocessing.AttributeNode

AVG - Static variable in class greycat.ml.preprocessing.AttributeNode

AVG - Static variable in class greycat.ml.profiling.Gaussian

avgLossPerOutput(DMatrix) - Static method in class greycat.ml.neuralnet.loss.Losses

avgOfLosses(DMatrix) - Static method in class greycat.ml.neuralnet.loss.Losses

B

backpropagate() - Method in class greycat.ml.neuralnet.process.ProcessGraph

backward(double, double) - Method in interface greycat.ml.neuralnet.activation.Activation

backward(ExMatrix, ExMatrix) - Method in class greycat.ml.neuralnet.loss.AbstractValue

backward(ExMatrix, ExMatrix) - Method in interface greycat.ml.neuralnet.loss.Loss

BaseMLNode - Class in greycat.ml

BaseMLNode(long, long, long, Graph) - Constructor for class greycat.ml.BaseMLNode

C

CENTER_ON_AVG - Static variable in class greycat.ml.preprocessing.PCA

clearProfile(Node) - Static method in class greycat.ml.profiling.Gaussian

clone(double[]) - Method in class greycat.ml.math.MultivariateNormalDistribution

column(int) - Method in class greycat.ml.neuralnet.process.ExMatrix

columns() - Method in class greycat.ml.neuralnet.process.ExMatrix

concatVectors(ExMatrix, ExMatrix) - Method in class greycat.ml.neuralnet.process.ProcessGraph

convertSpace(DMatrix) - Method in class greycat.ml.preprocessing.PCA

convertVector(double[]) - Method in class greycat.ml.preprocessing.PCA

COV - Static variable in class greycat.ml.profiling.Gaussian

createFromW(DMatrix) - Static method in class greycat.ml.neuralnet.process.ExMatrix

createLayer(ENode, int) - Static method in class greycat.ml.neuralnet.layer.Layers

D

data() - Method in class greycat.ml.neuralnet.process.ExMatrix

DEFAULT - Static variable in class greycat.ml.neuralnet.activation.Activations

DEFAULT - Static variable in class greycat.ml.neuralnet.loss.Losses

DEFAULT - Static variable in class greycat.ml.neuralnet.optimiser.Optimisers

density(double[], boolean) - Method in class greycat.ml.math.MultivariateNormalDistribution

densityExponent(double[]) - Method in class greycat.ml.math.MultivariateNormalDistribution

E

elmul(ExMatrix, ExMatrix) - Method in class greycat.ml.neuralnet.process.ProcessGraph

empty(int, int) - Static method in class greycat.ml.neuralnet.process.ExMatrix

EPS - Static variable in class greycat.ml.preprocessing.PCA

eval(TaskContext) - Method in class greycat.ml.actions.ActionTraverseOrKeep

eval(TaskContext) - Method in class greycat.ml.regression.actions.ReadContinuous

eval(TaskContext) - Method in class greycat.ml.regression.actions.SetContinuous

eval(TaskContext) - Method in class greycat.ml.regression.actions.SetPrecision

execute() - Method in interface greycat.ml.neuralnet.process.ProcessStep

ExMatrix - Class in greycat.ml.neuralnet.process

ExMatrix(ENode, String) - Constructor for class greycat.ml.neuralnet.process.ExMatrix

expand(ExMatrix, int) - Method in class greycat.ml.neuralnet.process.ProcessGraph

extractFeatures(Callback<double[]>) - Method in class greycat.ml.BaseMLNode

extrapolate(double, double[]) - Static method in class greycat.ml.math.PolynomialFit

EXTRAPOLATE - Static variable in class greycat.ml.preprocessing.AttributeNode

extrapolate(Callback<Double>) - Method in class greycat.ml.regression.PolynomialNode

extrapolate(Callback<Double>) - Method in interface greycat.ml.RegressionNode

Main infer function to give a cluster ID, The input features are defined through features extractions.

F

FEED_FORWARD_LAYER - Static variable in class greycat.ml.neuralnet.layer.Layers

fill(double) - Method in class greycat.ml.neuralnet.process.ExMatrix

fillWith(double[]) - Method in class greycat.ml.neuralnet.process.ExMatrix

finalLearn() - Method in class greycat.ml.neuralnet.NeuralNet

finalUpdate(Layer[]) - Method in interface greycat.ml.neuralnet.optimiser.Optimiser

fit(double[], double[]) - Method in class greycat.ml.math.PolynomialFit

forward(double) - Method in interface greycat.ml.neuralnet.activation.Activation

forward(ExMatrix, ProcessGraph) - Method in interface greycat.ml.neuralnet.layer.Layer

forward(ExMatrix, ExMatrix) - Method in class greycat.ml.neuralnet.loss.AbstractValue

forward(ExMatrix, ExMatrix) - Method in interface greycat.ml.neuralnet.loss.Loss

FROM - Static variable in class greycat.ml.BaseMLNode

FROM_SEPARATOR - Static variable in class greycat.ml.BaseMLNode

G

Gaussian - Class in greycat.ml.profiling

Created by assaad on 20/02/2017.

Gaussian() - Constructor for class greycat.ml.profiling.Gaussian

Gaussian1D - Class in greycat.ml.math

Gaussian1D() - Constructor for class greycat.ml.math.Gaussian1D

GaussianENode - Class in greycat.ml.profiling

GaussianENode(ENode) - Constructor for class greycat.ml.profiling.GaussianENode

GaussianNode - Class in greycat.ml.profiling

Created by assaad on 20/02/2017.

GaussianNode(long, long, long, Graph) - Constructor for class greycat.ml.profiling.GaussianNode

GaussianSlotsEGraph - Class in greycat.ml.profiling

Created by assaad on 20/02/2017.

GaussianSlotsEGraph(EGraph) - Constructor for class greycat.ml.profiling.GaussianSlotsEGraph

GaussianSlotsNode - Class in greycat.ml.profiling

GaussianSlotsNode(long, long, long, Graph) - Constructor for class greycat.ml.profiling.GaussianSlotsNode

get(int, int) - Method in class greycat.ml.neuralnet.process.ExMatrix

get(String) - Method in class greycat.ml.preprocessing.AttributeNode

get(String) - Method in class greycat.ml.profiling.GaussianNode

get(String) - Method in class greycat.ml.profiling.GaussianSlotsNode

get(String) - Method in class greycat.ml.regression.PolynomialNode

get_avg() - Method in class greycat.ml.preprocessing.PCA

get_bestDim() - Method in class greycat.ml.preprocessing.PCA

get_data() - Method in class greycat.ml.preprocessing.PCA

get_max() - Method in class greycat.ml.preprocessing.PCA

get_min() - Method in class greycat.ml.preprocessing.PCA

get_sigma() - Method in class greycat.ml.preprocessing.PCA

getAvg() - Method in class greycat.ml.math.MultivariateNormalDistribution

getAvg() - Method in class greycat.ml.profiling.GaussianENode

getCoef() - Method in class greycat.ml.math.PolynomialFit

getCovariance(double, double, long) - Static method in class greycat.ml.math.Gaussian1D

getCovariance(double[], double[], int) - Static method in class greycat.ml.math.MultivariateNormalDistribution

getCovariance() - Method in class greycat.ml.profiling.GaussianENode

getCovDiag() - Method in class greycat.ml.math.MultivariateNormalDistribution

getDensity(double, double, int, double) - Static method in class greycat.ml.math.Gaussian1D

getDensityArray(double, double, int, double[]) - Static method in class greycat.ml.math.Gaussian1D

getDimensionInfo() - Method in class greycat.ml.preprocessing.PCA

getDimensions() - Method in class greycat.ml.profiling.GaussianENode

getDistribution(double[], double[], int, boolean) - Static method in class greycat.ml.math.MultivariateNormalDistribution

getDw() - Method in class greycat.ml.neuralnet.process.ExMatrix

getGaussian(int) - Method in class greycat.ml.profiling.GaussianSlotsEGraph

getGeneric() - Method in class greycat.ml.profiling.GaussianSlotsEGraph

getIntTime(long, int, long) - Static method in class greycat.ml.profiling.GaussianSlotsNode

getLayerParameters() - Method in interface greycat.ml.neuralnet.layer.Layer

getMax() - Method in class greycat.ml.math.MultivariateNormalDistribution

getMax() - Method in class greycat.ml.profiling.GaussianENode

getMin() - Method in class greycat.ml.math.MultivariateNormalDistribution

getMin() - Method in class greycat.ml.profiling.GaussianENode

getPearson() - Method in class greycat.ml.profiling.GaussianENode

getPercentRetained() - Method in class greycat.ml.preprocessing.PCA

getPeriod(double[], int, int) - Static method in class greycat.ml.math.periodicity.PearsonPeriodicity

getSTD() - Method in class greycat.ml.profiling.GaussianENode

getStepCache() - Method in class greycat.ml.neuralnet.process.ExMatrix

getSum() - Method in class greycat.ml.profiling.GaussianENode

getSumSq() - Method in class greycat.ml.profiling.GaussianENode

getTotal() - Method in class greycat.ml.profiling.GaussianENode

getTransformationVector() - Method in class greycat.ml.preprocessing.PCA

getUnit(int, double[]) - Static method in class greycat.ml.neuralnet.activation.Activations

getUnit(int) - Static method in class greycat.ml.neuralnet.loss.Losses

getUnit(int, ENode) - Static method in class greycat.ml.neuralnet.optimiser.Optimisers

getW() - Method in class greycat.ml.neuralnet.process.ExMatrix

GRADIENT_DESCENT - Static variable in class greycat.ml.neuralnet.optimiser.Optimisers

greycat.ml - package greycat.ml

greycat.ml.actions - package greycat.ml.actions

greycat.ml.math - package greycat.ml.math

greycat.ml.math.periodicity - package greycat.ml.math.periodicity

greycat.ml.neuralnet - package greycat.ml.neuralnet

greycat.ml.neuralnet.activation - package greycat.ml.neuralnet.activation

greycat.ml.neuralnet.layer - package greycat.ml.neuralnet.layer

greycat.ml.neuralnet.loss - package greycat.ml.neuralnet.loss

greycat.ml.neuralnet.optimiser - package greycat.ml.neuralnet.optimiser

greycat.ml.neuralnet.process - package greycat.ml.neuralnet.process

greycat.ml.preprocessing - package greycat.ml.preprocessing

greycat.ml.profiling - package greycat.ml.profiling

greycat.ml.regression - package greycat.ml.regression

greycat.ml.regression.actions - package greycat.ml.regression.actions

GRU_LAYER - Static variable in class greycat.ml.neuralnet.layer.Layers

H

hasStepCache() - Method in class greycat.ml.neuralnet.process.ExMatrix

histogram(Node, double, double, Double, int) - Static method in class greycat.ml.profiling.Gaussian

HISTOGRAM_CENTER - Static variable in class greycat.ml.profiling.Gaussian

HISTOGRAM_VALUES - Static variable in class greycat.ml.profiling.Gaussian

I

illegalArgumentIfFalse(boolean, String) - Method in class greycat.ml.BaseMLNode

Asserts that condition is true.

init(int, int, int, double[], RandomGenerator, double) - Method in interface greycat.ml.neuralnet.layer.Layer

init(int, int) - Method in class greycat.ml.neuralnet.process.ExMatrix

inputDimensions() - Method in interface greycat.ml.neuralnet.layer.Layer

instance() - Static method in class greycat.ml.neuralnet.loss.AbstractValue

INTERNAL_STEP_KEY - Static variable in class greycat.ml.regression.PolynomialNode

INTERNAL_WEIGHT_KEY - Static variable in class greycat.ml.regression.PolynomialNode

inverseConvertSpace(DMatrix) - Method in class greycat.ml.preprocessing.PCA

inverseConvertVector(double[]) - Method in class greycat.ml.preprocessing.PCA

inverseNormalise(double[], double[], double[]) - Static method in class greycat.ml.profiling.Gaussian

inversenormaliseMatrix(DMatrix, double[], double[]) - Static method in class greycat.ml.profiling.Gaussian

inverseNormaliseMinMax(double[], double[], double[]) - Static method in class greycat.ml.profiling.Gaussian

inversenormaliseMinMaxMatrix(DMatrix, double[], double[]) - Static method in class greycat.ml.profiling.Gaussian

inverseNormaliseMinMaxValue(double, double, double) - Static method in class greycat.ml.profiling.Gaussian

inverseNormaliseValue(double, double, double) - Static method in class greycat.ml.profiling.Gaussian

inverseNormalizeData(DMatrix) - Method in class greycat.ml.preprocessing.PCA

inverseNormalizeError(DMatrix, double[]) - Static method in class greycat.ml.neuralnet.loss.Losses

IS_VALID - Static variable in class greycat.ml.preprocessing.AttributeNode

L

Layer - Interface in greycat.ml.neuralnet.layer

Layers - Class in greycat.ml.neuralnet.layer

Layers() - Constructor for class greycat.ml.neuralnet.layer.Layers

leadingDimension() - Method in class greycat.ml.neuralnet.process.ExMatrix

learn(double[], double[], boolean) - Method in class greycat.ml.neuralnet.NeuralNet

learn(double[]) - Method in class greycat.ml.profiling.GaussianENode

learn(double[]) - Method in class greycat.ml.profiling.GaussianNode

learn(int, double[]) - Method in class greycat.ml.profiling.GaussianSlotsEGraph

learn(double[]) - Method in class greycat.ml.profiling.GaussianSlotsNode

learn(Callback<Boolean>) - Method in interface greycat.ml.ProfilingNode

Main training function to learn from the the expected output, The input features are defined through features extractions.

learn(double, Callback<Boolean>) - Method in class greycat.ml.regression.PolynomialNode

learn(double, Callback<Boolean>) - Method in interface greycat.ml.RegressionNode

Main training function to learn from the the expected output, The input features are defined through features extractions.

learnVec(DMatrix, DMatrix, boolean) - Method in class greycat.ml.neuralnet.NeuralNet

learnWith(double[]) - Method in interface greycat.ml.ProfilingNode

length() - Method in class greycat.ml.neuralnet.process.ExMatrix

LINEAR - Static variable in class greycat.ml.neuralnet.activation.Activations

LINEAR_LAYER - Static variable in class greycat.ml.neuralnet.layer.Layers

load() - Method in class greycat.ml.profiling.GaussianSlotsEGraph

loadLayer(ENode) - Static method in class greycat.ml.neuralnet.layer.Layers

Loss - Interface in greycat.ml.neuralnet.loss

Losses - Class in greycat.ml.neuralnet.loss

Losses() - Constructor for class greycat.ml.neuralnet.loss.Losses

LSTM_LAYER - Static variable in class greycat.ml.neuralnet.layer.Layers

M

MAX - Static variable in class greycat.ml.profiling.Gaussian

MAX_DEGREE - Static variable in class greycat.ml.regression.PolynomialNode

MAX_DEGREE_DEF - Static variable in class greycat.ml.regression.PolynomialNode

MAX_OBSERVED - Static variable in class greycat.ml.preprocessing.AttributeNode

MAX_TOLERATED - Static variable in class greycat.ml.preprocessing.AttributeNode

MAX_VALID - Static variable in class greycat.ml.preprocessing.AttributeNode

MEAN_SQUARED_ERROR - Static variable in class greycat.ml.neuralnet.loss.Losses

MIN - Static variable in class greycat.ml.profiling.Gaussian

MIN_OBSERVED - Static variable in class greycat.ml.preprocessing.AttributeNode

MIN_TOLERATED - Static variable in class greycat.ml.preprocessing.AttributeNode

MIN_VALID - Static variable in class greycat.ml.preprocessing.AttributeNode

MLPlugin - Class in greycat.ml

MLPlugin() - Constructor for class greycat.ml.MLPlugin

MOMENTUM - Static variable in class greycat.ml.neuralnet.optimiser.Optimisers

mul(ExMatrix, ExMatrix) - Method in class greycat.ml.neuralnet.process.ProcessGraph

MULTI_DIM_BINARY - Static variable in class greycat.ml.neuralnet.loss.Losses

MultivariateNormalDistribution - Class in greycat.ml.math

MultivariateNormalDistribution(double[], DMatrix, boolean) - Constructor for class greycat.ml.math.MultivariateNormalDistribution

N

NAME - Static variable in class greycat.ml.actions.ActionTraverseOrKeep

name() - Method in class greycat.ml.actions.ActionTraverseOrKeep

NAME - Static variable in class greycat.ml.preprocessing.AttributeNode

NAME - Static variable in class greycat.ml.profiling.GaussianENode

NAME - Static variable in class greycat.ml.profiling.GaussianNode

NAME - Static variable in class greycat.ml.profiling.GaussianSlotsNode

NAME - Static variable in class greycat.ml.regression.actions.ReadContinuous

name() - Method in class greycat.ml.regression.actions.ReadContinuous

NAME - Static variable in class greycat.ml.regression.actions.SetContinuous

name() - Method in class greycat.ml.regression.actions.SetContinuous

NAME - Static variable in class greycat.ml.regression.actions.SetPrecision

name() - Method in class greycat.ml.regression.actions.SetPrecision

NAME - Static variable in class greycat.ml.regression.PolynomialNode

Name of the algorithm to be used in the meta model

NESTEROV - Static variable in class greycat.ml.neuralnet.optimiser.Optimisers

NeuralNet - Class in greycat.ml.neuralnet

NeuralNet(EGraph) - Constructor for class greycat.ml.neuralnet.NeuralNet

NOPROCESS - Static variable in class greycat.ml.preprocessing.PCA

normalise(double[], double[], double[]) - Static method in class greycat.ml.profiling.Gaussian

normaliseMatrix(DMatrix, double[], double[]) - Static method in class greycat.ml.profiling.Gaussian

normaliseMinMax(double[], double[], double[]) - Static method in class greycat.ml.profiling.Gaussian

normaliseMinMaxMatrix(DMatrix, double[], double[]) - Static method in class greycat.ml.profiling.Gaussian

normaliseMinMaxValue(double, double, double) - Static method in class greycat.ml.profiling.Gaussian

normaliseValue(double, double, double) - Static method in class greycat.ml.profiling.Gaussian

NORMALIZE - Static variable in class greycat.ml.preprocessing.PCA

normalizeData(DMatrix) - Method in class greycat.ml.preprocessing.PCA

NULL - Static variable in class greycat.ml.profiling.Gaussian

NUMBER_OF_SLOTS - Static variable in class greycat.ml.profiling.GaussianSlotsEGraph

NUMBER_OF_SLOTS - Static variable in class greycat.ml.profiling.GaussianSlotsNode

NUMBER_OF_SLOTS_DEF - Static variable in class greycat.ml.profiling.GaussianSlotsNode

O

oneMinus(ExMatrix) - Method in class greycat.ml.neuralnet.process.ProcessGraph

Optimiser - Interface in greycat.ml.neuralnet.optimiser

Created by assaad on 13/02/2017.

Optimisers - Class in greycat.ml.neuralnet.optimiser

Created by assaad on 13/02/2017.

Optimisers() - Constructor for class greycat.ml.neuralnet.optimiser.Optimisers

outputDimensions() - Method in interface greycat.ml.neuralnet.layer.Layer

P

PCA - Class in greycat.ml.preprocessing

PCA(DMatrix, int) - Constructor for class greycat.ml.preprocessing.PCA

PearsonPeriodicity - Class in greycat.ml.math.periodicity

Created by assaad on 08/03/2017.

PearsonPeriodicity() - Constructor for class greycat.ml.math.periodicity.PearsonPeriodicity

PERIOD_SIZE - Static variable in class greycat.ml.profiling.GaussianSlotsNode

PERIOD_SIZE_DEF - Static variable in class greycat.ml.profiling.GaussianSlotsNode

PolynomialFit - Class in greycat.ml.math

PolynomialFit(int) - Constructor for class greycat.ml.math.PolynomialFit

PolynomialNode - Class in greycat.ml.regression

PolynomialNode(long, long, long, Graph) - Constructor for class greycat.ml.regression.PolynomialNode

PRECISION - Static variable in class greycat.ml.regression.PolynomialNode

Tolerated error that can be configure per node to drive the learning process

PRECISION_DEF - Static variable in class greycat.ml.regression.PolynomialNode

PRECISIONS - Static variable in class greycat.ml.profiling.Gaussian

predict(double[]) - Method in class greycat.ml.neuralnet.NeuralNet

predict() - Method in class greycat.ml.profiling.GaussianNode

predict() - Method in class greycat.ml.profiling.GaussianSlotsNode

predict(Callback<double[]>) - Method in interface greycat.ml.ProfilingNode

Main infer function to give a cluster ID, The input features are defined through features extractions.

predictVec(DMatrix) - Method in class greycat.ml.neuralnet.NeuralNet

predictWith(double[], Callback<double[]>) - Method in interface greycat.ml.ProfilingNode

ProcessGraph - Class in greycat.ml.neuralnet.process

ProcessGraph(boolean) - Constructor for class greycat.ml.neuralnet.process.ProcessGraph

processRMSErr(DMatrix, int) - Static method in class greycat.ml.neuralnet.loss.Losses

ProcessStep - Interface in greycat.ml.neuralnet.process

profile(Node, Double, Double, Double) - Static method in class greycat.ml.profiling.Gaussian

ProfilingNode - Interface in greycat.ml

R

ReadContinuous - Class in greycat.ml.regression.actions

ReadContinuous(String) - Constructor for class greycat.ml.regression.actions.ReadContinuous

RECTIFIED_LINEAR - Static variable in class greycat.ml.neuralnet.activation.Activations

RegressionNode - Interface in greycat.ml

reInit(RandomGenerator, double) - Method in interface greycat.ml.neuralnet.layer.Layer

REJECT - Static variable in class greycat.ml.profiling.Gaussian

requireNotNull(Object, String) - Static method in class greycat.ml.BaseMLNode

If obj is null, throws NullPointerException with a message

resetState() - Method in interface greycat.ml.neuralnet.layer.Layer

resetState() - Method in class greycat.ml.neuralnet.NeuralNet

retain(double[], double) - Static method in class greycat.ml.preprocessing.PCA

rmse(double[], double[], double[]) - Static method in class greycat.ml.math.PolynomialFit

RMSPROP - Static variable in class greycat.ml.neuralnet.optimiser.Optimisers

RNN_LAYER - Static variable in class greycat.ml.neuralnet.layer.Layers

rows() - Method in class greycat.ml.neuralnet.process.ExMatrix

S

serialize(Buffer) - Method in class greycat.ml.actions.ActionTraverseOrKeep

serialize(Buffer) - Method in class greycat.ml.regression.actions.ReadContinuous

serialize(Buffer) - Method in class greycat.ml.regression.actions.SetContinuous

serialize(Buffer) - Method in class greycat.ml.regression.actions.SetPrecision

set(int, int, double) - Method in class greycat.ml.neuralnet.process.ExMatrix

set(String, byte, Object) - Method in class greycat.ml.preprocessing.AttributeNode

set(String, byte, Object) - Method in class greycat.ml.profiling.GaussianNode

set(String, byte, Object) - Method in class greycat.ml.profiling.GaussianSlotsNode

set(String, byte, Object) - Method in class greycat.ml.regression.PolynomialNode

setBackPropagation(boolean) - Method in class greycat.ml.neuralnet.process.ProcessGraph

setBatchSize(int) - Method in interface greycat.ml.neuralnet.optimiser.Optimiser

SetContinuous - Class in greycat.ml.regression.actions

SetContinuous(String, String) - Constructor for class greycat.ml.regression.actions.SetContinuous

setDimension(int) - Method in class greycat.ml.preprocessing.PCA

setFrequency(int) - Method in interface greycat.ml.neuralnet.optimiser.Optimiser

setMax(double[]) - Method in class greycat.ml.math.MultivariateNormalDistribution

setMin(double[]) - Method in class greycat.ml.math.MultivariateNormalDistribution

setNumberOfSlots(int) - Method in class greycat.ml.profiling.GaussianSlotsEGraph

setOptimizer(int, double[], int) - Method in class greycat.ml.neuralnet.NeuralNet

setParams(double[]) - Method in class greycat.ml.neuralnet.optimiser.AdaDelta

setParams(double[]) - Method in interface greycat.ml.neuralnet.optimiser.Optimiser

SetPrecision - Class in greycat.ml.regression.actions

SetPrecision(String, String) - Constructor for class greycat.ml.regression.actions.SetPrecision

setPrecisions(double[]) - Method in class greycat.ml.profiling.GaussianENode

setRandom(long, double) - Method in class greycat.ml.neuralnet.NeuralNet

setTestLoss(int) - Method in class greycat.ml.neuralnet.NeuralNet

setTrainLoss(int) - Method in class greycat.ml.neuralnet.NeuralNet

SIGMA - Static variable in class greycat.ml.preprocessing.AttributeNode

SIGMOID - Static variable in class greycat.ml.neuralnet.activation.Activations

SINE - Static variable in class greycat.ml.neuralnet.activation.Activations

SOFTMAX - Static variable in class greycat.ml.neuralnet.loss.Losses

start(Graph) - Method in class greycat.ml.MLPlugin

STATUS_ACCEPTED - Static variable in class greycat.ml.profiling.Gaussian

STATUS_NULL - Static variable in class greycat.ml.profiling.Gaussian

STATUS_REJECTED - Static variable in class greycat.ml.profiling.Gaussian

STD - Static variable in class greycat.ml.profiling.Gaussian

stepUpdate(Layer[]) - Method in interface greycat.ml.neuralnet.optimiser.Optimiser

stop() - Method in class greycat.ml.MLPlugin

SUM - Static variable in class greycat.ml.profiling.Gaussian

SUM_OF_SQUARES - Static variable in class greycat.ml.neuralnet.loss.Losses

sumOfLosses(DMatrix) - Static method in class greycat.ml.neuralnet.loss.Losses

sumOverOutputs(DMatrix) - Static method in class greycat.ml.neuralnet.loss.Losses

sumOverOutputsMatrix(DMatrix) - Static method in class greycat.ml.neuralnet.loss.Losses

SUMSQ - Static variable in class greycat.ml.profiling.Gaussian

T

TANH - Static variable in class greycat.ml.neuralnet.activation.Activations

testVec(DMatrix, DMatrix) - Method in class greycat.ml.neuralnet.NeuralNet

TIME_SENSITIVITY_FACTOR - Static variable in class greycat.ml.profiling.GaussianSlotsNode

toString() - Method in class greycat.ml.regression.PolynomialNode

TOTAL - Static variable in class greycat.ml.preprocessing.AttributeNode

TOTAL - Static variable in class greycat.ml.profiling.Gaussian

TOTAL_VALID - Static variable in class greycat.ml.preprocessing.AttributeNode

Trainer - Class in greycat.ml.neuralnet.process

Trainer() - Constructor for class greycat.ml.neuralnet.process.Trainer

TYPE - Static variable in class greycat.ml.neuralnet.layer.Layers

U

unsafeGet(int) - Method in class greycat.ml.neuralnet.process.ExMatrix

unsafeSet(int, double) - Method in class greycat.ml.neuralnet.process.ExMatrix

update(Layer[]) - Method in class greycat.ml.neuralnet.optimiser.AdaDelta

V

VALID_VALUE - Static variable in class greycat.ml.preprocessing.AttributeNode

VALUE - Static variable in class greycat.ml.preprocessing.AttributeNode

VALUE - Static variable in class greycat.ml.regression.PolynomialNode

VALUES - Static variable in class greycat.ml.profiling.Gaussian

A B C D E F G H I L M N O P R S T U V