Package | Description |
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oracle.pgx.api.mllib |
This package contains graph machine learning tools for use with PGX.
|
oracle.pgx.config.mllib |
This package contains APIs to all graph machine learning features of PGX.
|
oracle.pgx.config.mllib.batchgenerator |
This package contains APIs to batch generators.
|
Modifier and Type | Method and Description |
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SupervisedGraphWiseModelBuilder |
SupervisedGraphWiseModelBuilder.setBatchGenerator(BatchGenerator batchGenerator)
Sets the batch generator.
|
Modifier and Type | Field and Description |
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static BatchGenerator |
SupervisedGraphWiseModelConfig.DEFAULT_BATCH_GENERATOR
|
Modifier and Type | Method and Description |
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BatchGenerator |
SupervisedGraphWiseModelConfig.getBatchGenerator() |
Modifier and Type | Method and Description |
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void |
SupervisedGraphWiseModelConfig.setBatchGenerator(BatchGenerator batchGenerator) |
Constructor and Description |
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SupervisedGraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] convLayerConfigs, boolean standardize, boolean shuffle, java.util.List<java.lang.String> vertexInputPropertyNames, java.util.List<java.lang.String> edgeInputPropertyNames, java.util.List<java.util.Set<java.lang.String>> targetVertexLabelSets, boolean fitted, double trainingLoss, int inputFeatureDim, int edgeInputFeatureDim, oracle.pgx.config.mllib.SupervisedGraphWiseModelConfig.LossFunction lossFunction, LossFunction lossFunctionClass, BatchGenerator batchGenerator, GraphWisePredictionLayerConfig[] predictionLayerConfigs, boolean normalize, java.lang.String vertexTargetPropertyName, LabelMaps labelMaps, GraphWiseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant) |
Modifier and Type | Class and Description |
---|---|
class |
StandardBatchGenerator |
class |
StratifiedOversamplingBatchGenerator |