Package oracle.pgx.config.mllib

Class DeepWalkModelConfig

java.lang.Object

oracle.pgx.config.mllib.DeepWalkModelConfig

All Implemented Interfaces:

BaseModelConfig

public class DeepWalkModelConfig
extends java.lang.Object
implements BaseModelConfig

Constructor Summary

Constructors

Constructor	Description
DeepWalkModelConfig()
DeepWalkModelConfig(int minWordFrequency, int batchSize, int numEpochs, int layerSize, double learningRate, double minLearningRate, int windowSize, int walkLength, int walksPerVertex, double sampleRate, int negativeSample, java.lang.Double trainingLoss, PropertyType vertexIdPropertyType, java.lang.Long seed, boolean shuffle, boolean enableAccelerator)

Method Summary

Modifier and Type	Method	Description
int	getBatchSize()	Gets the batch size
int	getLayerSize()
double	getLearningRate()
java.lang.Double	getLoss()
double	getMinLearningRate()
int	getMinWordFrequency()
int	getNegativeSample()
int	getNumEpochs()	Gets the number of epochs to train the model
double	getSampleRate()
java.lang.Long	getSeed()	Gets the random seed
PropertyType	getVertexIdPropertyType()
int	getWalkLength()
int	getWalksPerVertex()
int	getWindowSize()
boolean	isEnableAccelerator()
boolean	isIgnoreIsolated()
boolean	isShuffle()	Gets whether the model will shuffle or not
void	setBatchSize(int batchSize)
void	setEnableAccelerator(boolean enableAccelerator)
void	setIgnoreIsolated(boolean ignoreIsolated)
void	setLayerSize(int layerSize)
void	setLearningRate(double learningRate)
void	setLoss(java.lang.Double trainingLoss)	Sets the loss after training
void	setMinLearningRate(double minLearningRate)
void	setMinWordFrequency(int minWordFrequency)
void	setNegativeSample(int negativeSample)
void	setNumEpochs(int numEpochs)
void	setSampleRate(double sampleRate)
void	setSeed(java.lang.Long seed)
void	setShuffle(boolean shuffle)
void	setVertexIdPropertyType(PropertyType vertexIdPropertyType)
void	setWalkLength(int walkLength)
void	setWalksPerVertex(int walksPerVertex)
void	setWindowSize(int windowSize)

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

DeepWalkModelConfig

public DeepWalkModelConfig()

DeepWalkModelConfig

public DeepWalkModelConfig(int minWordFrequency,
                           int batchSize,
                           int numEpochs,
                           int layerSize,
                           double learningRate,
                           double minLearningRate,
                           int windowSize,
                           int walkLength,
                           int walksPerVertex,
                           double sampleRate,
                           int negativeSample,
                           java.lang.Double trainingLoss,
                           PropertyType vertexIdPropertyType,
                           java.lang.Long seed,
                           boolean shuffle,
                           boolean enableAccelerator)

Method Detail

getLoss

public java.lang.Double getLoss()

setLoss

public void setLoss(java.lang.Double trainingLoss)

Description copied from interface: BaseModelConfig

Sets the loss after training

Specified by:

setLoss in interface BaseModelConfig

Parameters:

trainingLoss - the value of the training loss

getWalkLength

public int getWalkLength()

setWalkLength

public void setWalkLength(int walkLength)

getWalksPerVertex

public int getWalksPerVertex()

setWalksPerVertex

public void setWalksPerVertex(int walksPerVertex)

getMinWordFrequency

public int getMinWordFrequency()

setMinWordFrequency

public void setMinWordFrequency(int minWordFrequency)

getBatchSize

public int getBatchSize()

Description copied from interface: BaseModelConfig

Gets the batch size

Specified by:

getBatchSize in interface BaseModelConfig

Returns:

batch size

setBatchSize

public void setBatchSize(int batchSize)

getNumEpochs

public int getNumEpochs()

Description copied from interface: BaseModelConfig

Gets the number of epochs to train the model

Specified by:

getNumEpochs in interface BaseModelConfig

Returns:

number of epochs to train the model

setNumEpochs

public void setNumEpochs(int numEpochs)

getLayerSize

public int getLayerSize()

setLayerSize

public void setLayerSize(int layerSize)

getLearningRate

public double getLearningRate()

setLearningRate

public void setLearningRate(double learningRate)

getMinLearningRate

public double getMinLearningRate()

setMinLearningRate

public void setMinLearningRate(double minLearningRate)

getWindowSize

public int getWindowSize()

setWindowSize

public void setWindowSize(int windowSize)

getSampleRate

public double getSampleRate()

setSampleRate

public void setSampleRate(double sampleRate)

getNegativeSample

public int getNegativeSample()

setNegativeSample

public void setNegativeSample(int negativeSample)

isShuffle

public boolean isShuffle()

Description copied from interface: BaseModelConfig

Gets whether the model will shuffle or not

Specified by:

isShuffle in interface BaseModelConfig

Returns:

whether the model will shuffle or not

setShuffle

public void setShuffle(boolean shuffle)

getVertexIdPropertyType

public PropertyType getVertexIdPropertyType()

setVertexIdPropertyType

public void setVertexIdPropertyType(PropertyType vertexIdPropertyType)

getSeed

public java.lang.Long getSeed()

Description copied from interface: BaseModelConfig

Gets the random seed

Specified by:

getSeed in interface BaseModelConfig

Returns:

random seed

setSeed

public void setSeed(java.lang.Long seed)

isIgnoreIsolated

public boolean isIgnoreIsolated()

setIgnoreIsolated

public void setIgnoreIsolated(boolean ignoreIsolated)

setEnableAccelerator

public void setEnableAccelerator(boolean enableAccelerator)

isEnableAccelerator

public boolean isEnableAccelerator()