Uses of Class
oracle.pgx.config.mllib.inputconfig.InputPropertyConfig

Packages that use InputPropertyConfig

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.
oracle.pgx.config.mllib.inputconfig

Uses of InputPropertyConfig in oracle.pgx.api.mllib

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

Modifier and Type	Method and Description
Self	WiseModelBuilder.setEdgeInputPropertyConfigs(InputPropertyConfig... propertyConfigs) Set edge input property configs.
Self	WiseModelBuilder.setVertexInputPropertyConfigs(InputPropertyConfig... propertyConfigs) Set vertex input property configs.

Uses of InputPropertyConfig in oracle.pgx.config.mllib

Methods in oracle.pgx.config.mllib that return types with arguments of type InputPropertyConfig

Modifier and Type	Method and Description
java.util.Map<java.lang.String,InputPropertyConfig>	GraphWiseBaseModelConfig.getEdgeInputPropertyConfigs()
java.util.Map<java.lang.String,InputPropertyConfig>	GraphWiseBaseModelConfig.getVertexInputPropertyConfigs()

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

Modifier and Type	Method and Description
void	GraphWiseBaseModelConfig.setEdgeInputPropertyConfigs(InputPropertyConfig... edgeInputPropertyConfigs)
void	GraphWiseBaseModelConfig.setVertexInputPropertyConfigs(InputPropertyConfig... vertexInputPropertyConfigs)

Constructor parameters in oracle.pgx.config.mllib with type arguments of type InputPropertyConfig

Constructor and Description
EdgeWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] 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, boolean fitted, double trainingLoss, int vertexInputFeatureDim, int edgeInputFeatureDim, java.util.List<java.util.Set<java.lang.String>> targetEdgeLabelSets, GraphWiseBaseModelConfig.Backend backend, java.lang.Integer edgeEmbeddingDim, EdgeWiseModelConfig.EdgeWiseConvModelVariant variant, EdgeCombinationMethod edgeCombinationMethod)
EdgeWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] 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, boolean fitted, double trainingLoss, int vertexInputFeatureDim, int edgeInputFeatureDim, java.util.List<java.util.Set<java.lang.String>> targetEdgeLabelSets, GraphWiseBaseModelConfig.Backend backend, java.lang.Integer edgeEmbeddingDim, EdgeWiseModelConfig.EdgeWiseConvModelVariant variant, EdgeCombinationMethod edgeCombinationMethod)
GraphWiseBaseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] 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, boolean fitted, double trainingLoss, int vertexInputFeatureDim, int edgeInputFeatureDim, GraphWiseBaseModelConfig.Backend backend)
GraphWiseBaseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] 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, boolean fitted, double trainingLoss, int vertexInputFeatureDim, int edgeInputFeatureDim, GraphWiseBaseModelConfig.Backend backend)
GraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] 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, boolean fitted, double trainingLoss, int vertexInputFeatureDim, int edgeInputFeatureDim, java.util.List<java.util.Set<java.lang.String>> targetVertexLabelSets, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant)
GraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] 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, boolean fitted, double trainingLoss, int vertexInputFeatureDim, int edgeInputFeatureDim, java.util.List<java.util.Set<java.lang.String>> targetVertexLabelSets, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant)
SupervisedEdgeWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer edgeEmbeddingDim, 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.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)
SupervisedEdgeWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer edgeEmbeddingDim, 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.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)
SupervisedGraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] 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)
SupervisedGraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] 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)
UnsupervisedEdgeWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer edgeEmbeddingDim, 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.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, UnsupervisedEdgeWiseModelConfig.LossFunction lossFunction, boolean normalize, GraphWiseBaseModelConfig.Backend backend, EdgeCombinationMethod edgeCombinationMethod, EdgeWiseModelConfig.EdgeWiseConvModelVariant variant, GraphWiseDgiLayerConfig dgiLayerConfig)
UnsupervisedEdgeWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer edgeEmbeddingDim, 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.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, UnsupervisedEdgeWiseModelConfig.LossFunction lossFunction, boolean normalize, GraphWiseBaseModelConfig.Backend backend, EdgeCombinationMethod edgeCombinationMethod, EdgeWiseModelConfig.EdgeWiseConvModelVariant variant, GraphWiseDgiLayerConfig dgiLayerConfig)
UnsupervisedGraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] 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>> targetVertexLabels, boolean fitted, double trainingLoss, int inputFeatureDim, int inputEdgeFeatureDim, UnsupervisedGraphWiseModelConfig.LossFunction lossFunction, GraphWiseDgiLayerConfig dgiLayerConfig, GraphWiseEmbeddingConfig embeddingConfig, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant)
UnsupervisedGraphWiseModelConfig(int batchSize, int numEpochs, double learningRate, double weightDecay, int embeddingDim, java.lang.Integer seed, GraphWiseConvLayerConfig[] 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>> targetVertexLabels, boolean fitted, double trainingLoss, int inputFeatureDim, int inputEdgeFeatureDim, UnsupervisedGraphWiseModelConfig.LossFunction lossFunction, GraphWiseDgiLayerConfig dgiLayerConfig, GraphWiseEmbeddingConfig embeddingConfig, GraphWiseBaseModelConfig.Backend backend, GraphWiseModelConfig.GraphConvModelVariant variant)

Uses of InputPropertyConfig in oracle.pgx.config.mllib.inputconfig

Subclasses of InputPropertyConfig in oracle.pgx.config.mllib.inputconfig

Modifier and Type	Class and Description
class	CategoricalPropertyConfig Configuration class for categorical feature handling.
class	ContinuousPropertyConfig Configuration class for continuous feature handling.
class	EmbeddingTableConfig Configuration class for handling categorical feature using embedding table method.
class	OneHotEncodingConfig Configuration class for handling categorical feature using one hot encoding method.

Constructors in oracle.pgx.config.mllib.inputconfig with parameters of type InputPropertyConfig

Constructor and Description
InputPropertyConfig(InputPropertyConfig otherConfig)