Uses of Class
com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Builder
Packages that use AutoMlForecastingInputs.Builder
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Uses of AutoMlForecastingInputs.Builder in com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition
Methods in com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition that return AutoMlForecastingInputs.BuilderModifier and TypeMethodDescriptionAutoMlForecastingInputs.Builder.addAdditionalExperiments(String value) Additional experiment flags for the time series forcasting training.AutoMlForecastingInputs.Builder.addAdditionalExperimentsBytes(com.google.protobuf.ByteString value) Additional experiment flags for the time series forcasting training.AutoMlForecastingInputs.Builder.addAllAdditionalExperiments(Iterable<String> values) Additional experiment flags for the time series forcasting training.AutoMlForecastingInputs.Builder.addAllAvailableAtForecastColumns(Iterable<String> values) Names of columns that are available and provided when a forecast is requested.AutoMlForecastingInputs.Builder.addAllQuantiles(Iterable<? extends Double> values) Quantiles to use for minimize-quantile-loss `optimization_objective`.AutoMlForecastingInputs.Builder.addAllTimeSeriesAttributeColumns(Iterable<String> values) Column names that should be used as attribute columns.AutoMlForecastingInputs.Builder.addAllTransformations(Iterable<? extends AutoMlForecastingInputs.Transformation> values) Each transformation will apply transform function to given input column.AutoMlForecastingInputs.Builder.addAllUnavailableAtForecastColumns(Iterable<String> values) Names of columns that are unavailable when a forecast is requested.AutoMlForecastingInputs.Builder.addAvailableAtForecastColumns(String value) Names of columns that are available and provided when a forecast is requested.AutoMlForecastingInputs.Builder.addAvailableAtForecastColumnsBytes(com.google.protobuf.ByteString value) Names of columns that are available and provided when a forecast is requested.AutoMlForecastingInputs.Builder.addQuantiles(double value) Quantiles to use for minimize-quantile-loss `optimization_objective`.AutoMlForecastingInputs.Builder.addTimeSeriesAttributeColumns(String value) Column names that should be used as attribute columns.AutoMlForecastingInputs.Builder.addTimeSeriesAttributeColumnsBytes(com.google.protobuf.ByteString value) Column names that should be used as attribute columns.AutoMlForecastingInputs.Builder.addTransformations(int index, AutoMlForecastingInputs.Transformation value) Each transformation will apply transform function to given input column.AutoMlForecastingInputs.Builder.addTransformations(int index, AutoMlForecastingInputs.Transformation.Builder builderForValue) Each transformation will apply transform function to given input column.AutoMlForecastingInputs.Builder.addTransformations(AutoMlForecastingInputs.Transformation value) Each transformation will apply transform function to given input column.AutoMlForecastingInputs.Builder.addTransformations(AutoMlForecastingInputs.Transformation.Builder builderForValue) Each transformation will apply transform function to given input column.AutoMlForecastingInputs.Builder.addUnavailableAtForecastColumns(String value) Names of columns that are unavailable when a forecast is requested.AutoMlForecastingInputs.Builder.addUnavailableAtForecastColumnsBytes(com.google.protobuf.ByteString value) Names of columns that are unavailable when a forecast is requested.AutoMlForecastingInputs.Builder.clear()AutoMlForecastingInputs.Builder.clearAdditionalExperiments()Additional experiment flags for the time series forcasting training.AutoMlForecastingInputs.Builder.clearAvailableAtForecastColumns()Names of columns that are available and provided when a forecast is requested.AutoMlForecastingInputs.Builder.clearContextWindow()The amount of time into the past training and prediction data is used for model training and prediction respectively.AutoMlForecastingInputs.Builder.clearDataGranularity()Expected difference in time granularity between rows in the data.AutoMlForecastingInputs.Builder.clearExportEvaluatedDataItemsConfig()Configuration for exporting test set predictions to a BigQuery table.AutoMlForecastingInputs.Builder.clearForecastHorizon()The amount of time into the future for which forecasted values for the target are returned.AutoMlForecastingInputs.Builder.clearOptimizationObjective()Objective function the model is optimizing towards.AutoMlForecastingInputs.Builder.clearQuantiles()Quantiles to use for minimize-quantile-loss `optimization_objective`.AutoMlForecastingInputs.Builder.clearTargetColumn()The name of the column that the model is to predict.AutoMlForecastingInputs.Builder.clearTimeColumn()The name of the column that identifies time order in the time series.AutoMlForecastingInputs.Builder.clearTimeSeriesAttributeColumns()Column names that should be used as attribute columns.AutoMlForecastingInputs.Builder.clearTimeSeriesIdentifierColumn()The name of the column that identifies the time series.AutoMlForecastingInputs.Builder.clearTrainBudgetMilliNodeHours()Required.AutoMlForecastingInputs.Builder.clearTransformations()Each transformation will apply transform function to given input column.AutoMlForecastingInputs.Builder.clearUnavailableAtForecastColumns()Names of columns that are unavailable when a forecast is requested.AutoMlForecastingInputs.Builder.clearValidationOptions()Validation options for the data validation component.AutoMlForecastingInputs.Builder.clearWeightColumn()Column name that should be used as the weight column.AutoMlForecasting.Builder.getInputsBuilder()The input parameters of this TrainingJob.AutoMlForecastingInputs.Builder.mergeDataGranularity(AutoMlForecastingInputs.Granularity value) Expected difference in time granularity between rows in the data.AutoMlForecastingInputs.Builder.mergeExportEvaluatedDataItemsConfig(ExportEvaluatedDataItemsConfig value) Configuration for exporting test set predictions to a BigQuery table.AutoMlForecastingInputs.Builder.mergeFrom(AutoMlForecastingInputs other) AutoMlForecastingInputs.Builder.mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) AutoMlForecastingInputs.Builder.mergeFrom(com.google.protobuf.Message other) AutoMlForecastingInputs.newBuilder()AutoMlForecastingInputs.newBuilder(AutoMlForecastingInputs prototype) AutoMlForecastingInputs.newBuilderForType()protected AutoMlForecastingInputs.BuilderAutoMlForecastingInputs.newBuilderForType(com.google.protobuf.AbstractMessage.BuilderParent parent) AutoMlForecastingInputs.Builder.removeTransformations(int index) Each transformation will apply transform function to given input column.AutoMlForecastingInputs.Builder.setAdditionalExperiments(int index, String value) Additional experiment flags for the time series forcasting training.AutoMlForecastingInputs.Builder.setAvailableAtForecastColumns(int index, String value) Names of columns that are available and provided when a forecast is requested.AutoMlForecastingInputs.Builder.setContextWindow(long value) The amount of time into the past training and prediction data is used for model training and prediction respectively.AutoMlForecastingInputs.Builder.setDataGranularity(AutoMlForecastingInputs.Granularity value) Expected difference in time granularity between rows in the data.AutoMlForecastingInputs.Builder.setDataGranularity(AutoMlForecastingInputs.Granularity.Builder builderForValue) Expected difference in time granularity between rows in the data.AutoMlForecastingInputs.Builder.setExportEvaluatedDataItemsConfig(ExportEvaluatedDataItemsConfig value) Configuration for exporting test set predictions to a BigQuery table.AutoMlForecastingInputs.Builder.setExportEvaluatedDataItemsConfig(ExportEvaluatedDataItemsConfig.Builder builderForValue) Configuration for exporting test set predictions to a BigQuery table.AutoMlForecastingInputs.Builder.setForecastHorizon(long value) The amount of time into the future for which forecasted values for the target are returned.AutoMlForecastingInputs.Builder.setOptimizationObjective(String value) Objective function the model is optimizing towards.AutoMlForecastingInputs.Builder.setOptimizationObjectiveBytes(com.google.protobuf.ByteString value) Objective function the model is optimizing towards.AutoMlForecastingInputs.Builder.setQuantiles(int index, double value) Quantiles to use for minimize-quantile-loss `optimization_objective`.AutoMlForecastingInputs.Builder.setTargetColumn(String value) The name of the column that the model is to predict.AutoMlForecastingInputs.Builder.setTargetColumnBytes(com.google.protobuf.ByteString value) The name of the column that the model is to predict.AutoMlForecastingInputs.Builder.setTimeColumn(String value) The name of the column that identifies time order in the time series.AutoMlForecastingInputs.Builder.setTimeColumnBytes(com.google.protobuf.ByteString value) The name of the column that identifies time order in the time series.AutoMlForecastingInputs.Builder.setTimeSeriesAttributeColumns(int index, String value) Column names that should be used as attribute columns.AutoMlForecastingInputs.Builder.setTimeSeriesIdentifierColumn(String value) The name of the column that identifies the time series.AutoMlForecastingInputs.Builder.setTimeSeriesIdentifierColumnBytes(com.google.protobuf.ByteString value) The name of the column that identifies the time series.AutoMlForecastingInputs.Builder.setTrainBudgetMilliNodeHours(long value) Required.AutoMlForecastingInputs.Builder.setTransformations(int index, AutoMlForecastingInputs.Transformation value) Each transformation will apply transform function to given input column.AutoMlForecastingInputs.Builder.setTransformations(int index, AutoMlForecastingInputs.Transformation.Builder builderForValue) Each transformation will apply transform function to given input column.AutoMlForecastingInputs.Builder.setUnavailableAtForecastColumns(int index, String value) Names of columns that are unavailable when a forecast is requested.AutoMlForecastingInputs.Builder.setValidationOptions(String value) Validation options for the data validation component.AutoMlForecastingInputs.Builder.setValidationOptionsBytes(com.google.protobuf.ByteString value) Validation options for the data validation component.AutoMlForecastingInputs.Builder.setWeightColumn(String value) Column name that should be used as the weight column.AutoMlForecastingInputs.Builder.setWeightColumnBytes(com.google.protobuf.ByteString value) Column name that should be used as the weight column.AutoMlForecastingInputs.toBuilder()Methods in com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition with parameters of type AutoMlForecastingInputs.BuilderModifier and TypeMethodDescriptionAutoMlForecasting.Builder.setInputs(AutoMlForecastingInputs.Builder builderForValue) The input parameters of this TrainingJob.