Uses of Class
oracle.pgx.config.mllib.GraphWisePredictionLayerConfig

Packages that use GraphWisePredictionLayerConfig

Package	Description
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.

Uses of GraphWisePredictionLayerConfig in oracle.pgx.api.mllib

Methods in oracle.pgx.api.mllib that return GraphWisePredictionLayerConfig

Modifier and Type	Method	Description
GraphWisePredictionLayerConfig	GraphWisePredictionLayerConfigBuilder.build()	Build the configuration
GraphWisePredictionLayerConfig[]	SupervisedEdgeWiseModel.getPredictionLayerConfigs()	Gets the configuration objects for the prediction layers
GraphWisePredictionLayerConfig[]	SupervisedGraphWiseModel.getPredictionLayerConfigs()	Gets the configuration objects for the prediction layers

Methods in oracle.pgx.api.mllib with parameters of type GraphWisePredictionLayerConfig

Modifier and Type	Method	Description
GraphWiseDominantLayerConfigBuilder	GraphWiseDominantLayerConfigBuilder.setDecoderLayerConfigs(GraphWisePredictionLayerConfig... layerConfigs)	Set the decoder layer configurations (See GraphWisePredictionLayerConfig.
SupervisedEdgeWiseModelBuilder	SupervisedEdgeWiseModelBuilder.setPredictionLayerConfigs(GraphWisePredictionLayerConfig... layerConfigs)	Set the prediction layer configurations (See GraphWisePredictionLayerConfig.
SupervisedGraphWiseModelBuilder	SupervisedGraphWiseModelBuilder.setPredictionLayerConfigs(GraphWisePredictionLayerConfig... layerConfigs)	Set the prediction layer configurations (See GraphWisePredictionLayerConfig.

Uses of GraphWisePredictionLayerConfig in oracle.pgx.config.mllib

Fields in oracle.pgx.config.mllib declared as GraphWisePredictionLayerConfig

Modifier and Type	Field	Description
static GraphWisePredictionLayerConfig[]	GraphWiseDominantLayerConfig.DEFAULT_PREDICTION_LAYER_CONFIGS	by default no prediction layer config
static GraphWisePredictionLayerConfig[]	SupervisedEdgeWiseModelConfig.DEFAULT_PREDICTION_LAYER_CONFIGS	one default initialized config (See GraphWisePredictionLayerConfig)
static GraphWisePredictionLayerConfig[]	SupervisedGraphWiseModelConfig.DEFAULT_PREDICTION_LAYER_CONFIGS	one default initialized config (See GraphWisePredictionLayerConfig)

Methods in oracle.pgx.config.mllib that return GraphWisePredictionLayerConfig

Modifier and Type	Method	Description
GraphWisePredictionLayerConfig[]	GraphWiseDominantLayerConfig.getdecoderLayerConfigs()	Gets the configuration objects for the decoder layers
GraphWisePredictionLayerConfig[]	SupervisedEdgeWiseModelConfig.getPredictionLayerConfigs()
GraphWisePredictionLayerConfig[]	SupervisedGraphWiseModelConfig.getPredictionLayerConfigs()

Methods in oracle.pgx.config.mllib with parameters of type GraphWisePredictionLayerConfig

Modifier and Type	Method	Description
void	GraphWiseDominantLayerConfig.setDecoderLayerConfigs(GraphWisePredictionLayerConfig... decoderLayerConfigs)	Sets the configuration objects for the decoder layers
void	SupervisedEdgeWiseModelConfig.setPredictionLayerConfigs(GraphWisePredictionLayerConfig... predictionLayerConfigs)
void	SupervisedGraphWiseModelConfig.setPredictionLayerConfigs(GraphWisePredictionLayerConfig... predictionLayerConfigs)

Constructors in oracle.pgx.config.mllib with parameters of type GraphWisePredictionLayerConfig

Constructor	Description
SupervisedEdgeWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer edgeEmbeddingDim, java.lang.Integer seed, GraphWiseBaseConvLayerConfig[] convLayerConfigs, boolean standardize, boolean shuffle, java.util.List<java.lang.String> vertexInputPropertyNames, java.util.List<java.lang.String> edgeInputPropertyNames, java.util.Map<java.lang.String,InputPropertyConfig> vertexInputPropertyConfigs, java.util.Map<java.lang.String,InputPropertyConfig> edgeInputPropertyConfigs, oracle.pgx.config.internal.categorymapping.CategoryMappingConfig categoryMappingConfig, java.util.List<java.util.Set<java.lang.String>> targetEdgeLabelSets, boolean fitted, double trainingLoss, int inputFeatureDim, int edgeInputFeatureDim, oracle.pgx.config.mllib.SupervisedEdgeWiseModelConfig.LossFunction lossFunction, LossFunction lossFunctionClass, BatchGenerator batchGenerator, GraphWisePredictionLayerConfig[] predictionLayerConfigs, boolean normalize, java.lang.String edgeTargetPropertyName, LabelMaps labelMaps, GraphWiseBaseModelConfig.Backend backend, EdgeCombinationMethod edgeCombinationMethod, EdgeWiseModelConfig.EdgeWiseConvModelVariant variant, boolean enableAccelerator)
SupervisedGraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseBaseConvLayerConfig[] convLayerConfigs, boolean standardize, boolean normalize, boolean shuffle, java.util.List<java.lang.String> vertexInputPropertyNames, java.util.List<java.lang.String> edgeInputPropertyNames, java.util.Map<java.lang.String,InputPropertyConfig> vertexInputPropertyConfigs, java.util.Map<java.lang.String,InputPropertyConfig> edgeInputPropertyConfigs, oracle.pgx.config.internal.categorymapping.CategoryMappingConfig categoryMappingConfig, 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, java.lang.String vertexTargetPropertyName, LabelMaps labelMaps, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant, boolean enableAccelerator)