Class AutoMlForecastingInputs
java.lang.Object
com.google.protobuf.AbstractMessageLite
com.google.protobuf.AbstractMessage
com.google.protobuf.GeneratedMessage
com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs
- All Implemented Interfaces:
AutoMlForecastingInputsOrBuilder,com.google.protobuf.Message,com.google.protobuf.MessageLite,com.google.protobuf.MessageLiteOrBuilder,com.google.protobuf.MessageOrBuilder,Serializable
@Generated
public final class AutoMlForecastingInputs
extends com.google.protobuf.GeneratedMessage
implements AutoMlForecastingInputsOrBuilder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs- See Also:
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Nested Class Summary
Nested ClassesModifier and TypeClassDescriptionstatic final classProtobuf typegoogle.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputsstatic final classA duration of time expressed in time granularity units.static interfacestatic final classProtobuf typegoogle.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformationstatic interfaceNested classes/interfaces inherited from class com.google.protobuf.GeneratedMessage
com.google.protobuf.GeneratedMessage.ExtendableBuilder<MessageT extends com.google.protobuf.GeneratedMessage.ExtendableMessage<MessageT>,BuilderT extends com.google.protobuf.GeneratedMessage.ExtendableBuilder<MessageT, BuilderT>>, com.google.protobuf.GeneratedMessage.ExtendableMessage<MessageT extends com.google.protobuf.GeneratedMessage.ExtendableMessage<MessageT>>, com.google.protobuf.GeneratedMessage.ExtendableMessageOrBuilder<MessageT extends com.google.protobuf.GeneratedMessage.ExtendableMessage<MessageT>>, com.google.protobuf.GeneratedMessage.FieldAccessorTable, com.google.protobuf.GeneratedMessage.GeneratedExtension<ContainingT extends com.google.protobuf.Message, T extends Object>, com.google.protobuf.GeneratedMessage.UnusedPrivateParameter Nested classes/interfaces inherited from class com.google.protobuf.AbstractMessage
com.google.protobuf.AbstractMessage.BuilderParentNested classes/interfaces inherited from class com.google.protobuf.AbstractMessageLite
com.google.protobuf.AbstractMessageLite.InternalOneOfEnum -
Field Summary
FieldsModifier and TypeFieldDescriptionstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intstatic final intFields inherited from class com.google.protobuf.GeneratedMessage
alwaysUseFieldBuilders, loggedPre22TypeNames, unknownFieldsFields inherited from class com.google.protobuf.AbstractMessage
memoizedSizeFields inherited from class com.google.protobuf.AbstractMessageLite
memoizedHashCode -
Method Summary
Modifier and TypeMethodDescriptionbooleangetAdditionalExperiments(int index) Additional experiment flags for the time series forcasting training.com.google.protobuf.ByteStringgetAdditionalExperimentsBytes(int index) Additional experiment flags for the time series forcasting training.intAdditional experiment flags for the time series forcasting training.com.google.protobuf.ProtocolStringListAdditional experiment flags for the time series forcasting training.getAvailableAtForecastColumns(int index) Names of columns that are available and provided when a forecast is requested.com.google.protobuf.ByteStringgetAvailableAtForecastColumnsBytes(int index) Names of columns that are available and provided when a forecast is requested.intNames of columns that are available and provided when a forecast is requested.com.google.protobuf.ProtocolStringListNames of columns that are available and provided when a forecast is requested.longThe amount of time into the past training and prediction data is used for model training and prediction respectively.Expected difference in time granularity between rows in the data.Expected difference in time granularity between rows in the data.static AutoMlForecastingInputsstatic final com.google.protobuf.Descriptors.DescriptorConfiguration for exporting test set predictions to a BigQuery table.Configuration for exporting test set predictions to a BigQuery table.longThe amount of time into the future for which forecasted values for the target are returned.Objective function the model is optimizing towards.com.google.protobuf.ByteStringObjective function the model is optimizing towards.com.google.protobuf.Parser<AutoMlForecastingInputs>doublegetQuantiles(int index) Quantiles to use for minimize-quantile-loss `optimization_objective`.intQuantiles to use for minimize-quantile-loss `optimization_objective`.Quantiles to use for minimize-quantile-loss `optimization_objective`.intThe name of the column that the model is to predict.com.google.protobuf.ByteStringThe name of the column that the model is to predict.The name of the column that identifies time order in the time series.com.google.protobuf.ByteStringThe name of the column that identifies time order in the time series.getTimeSeriesAttributeColumns(int index) Column names that should be used as attribute columns.com.google.protobuf.ByteStringgetTimeSeriesAttributeColumnsBytes(int index) Column names that should be used as attribute columns.intColumn names that should be used as attribute columns.com.google.protobuf.ProtocolStringListColumn names that should be used as attribute columns.The name of the column that identifies the time series.com.google.protobuf.ByteStringThe name of the column that identifies the time series.longRequired.getTransformations(int index) Each transformation will apply transform function to given input column.intEach transformation will apply transform function to given input column.Each transformation will apply transform function to given input column.getTransformationsOrBuilder(int index) Each transformation will apply transform function to given input column.Each transformation will apply transform function to given input column.getUnavailableAtForecastColumns(int index) Names of columns that are unavailable when a forecast is requested.com.google.protobuf.ByteStringgetUnavailableAtForecastColumnsBytes(int index) Names of columns that are unavailable when a forecast is requested.intNames of columns that are unavailable when a forecast is requested.com.google.protobuf.ProtocolStringListNames of columns that are unavailable when a forecast is requested.Validation options for the data validation component.com.google.protobuf.ByteStringValidation options for the data validation component.Column name that should be used as the weight column.com.google.protobuf.ByteStringColumn name that should be used as the weight column.booleanExpected difference in time granularity between rows in the data.booleanConfiguration for exporting test set predictions to a BigQuery table.inthashCode()protected com.google.protobuf.GeneratedMessage.FieldAccessorTablefinal booleannewBuilder(AutoMlForecastingInputs prototype) protected AutoMlForecastingInputs.BuildernewBuilderForType(com.google.protobuf.AbstractMessage.BuilderParent parent) static AutoMlForecastingInputsparseDelimitedFrom(InputStream input) static AutoMlForecastingInputsparseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static AutoMlForecastingInputsparseFrom(byte[] data) static AutoMlForecastingInputsparseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static AutoMlForecastingInputsparseFrom(com.google.protobuf.ByteString data) static AutoMlForecastingInputsparseFrom(com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static AutoMlForecastingInputsparseFrom(com.google.protobuf.CodedInputStream input) static AutoMlForecastingInputsparseFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static AutoMlForecastingInputsparseFrom(InputStream input) static AutoMlForecastingInputsparseFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static AutoMlForecastingInputsparseFrom(ByteBuffer data) static AutoMlForecastingInputsparseFrom(ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static com.google.protobuf.Parser<AutoMlForecastingInputs>parser()voidwriteTo(com.google.protobuf.CodedOutputStream output) Methods inherited from class com.google.protobuf.GeneratedMessage
canUseUnsafe, computeStringSize, computeStringSizeNoTag, emptyBooleanList, emptyDoubleList, emptyFloatList, emptyIntList, emptyList, emptyLongList, getAllFields, getDescriptorForType, getField, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, isStringEmpty, makeExtensionsImmutable, makeMutableCopy, makeMutableCopy, mergeFromAndMakeImmutableInternal, newFileScopedGeneratedExtension, newInstance, newMessageScopedGeneratedExtension, parseDelimitedWithIOException, parseDelimitedWithIOException, parseUnknownField, parseUnknownFieldProto3, parseWithIOException, parseWithIOException, parseWithIOException, parseWithIOException, serializeBooleanMapTo, serializeIntegerMapTo, serializeLongMapTo, serializeStringMapTo, writeReplace, writeString, writeStringNoTagMethods inherited from class com.google.protobuf.AbstractMessage
findInitializationErrors, getInitializationErrorString, hashFields, toStringMethods inherited from class com.google.protobuf.AbstractMessageLite
addAll, checkByteStringIsUtf8, toByteArray, toByteString, writeDelimitedTo, writeToMethods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, waitMethods inherited from interface com.google.protobuf.MessageLite
toByteArray, toByteString, writeDelimitedTo, writeToMethods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
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Field Details
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TARGET_COLUMN_FIELD_NUMBER
public static final int TARGET_COLUMN_FIELD_NUMBER- See Also:
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TIME_SERIES_IDENTIFIER_COLUMN_FIELD_NUMBER
public static final int TIME_SERIES_IDENTIFIER_COLUMN_FIELD_NUMBER- See Also:
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TIME_COLUMN_FIELD_NUMBER
public static final int TIME_COLUMN_FIELD_NUMBER- See Also:
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TRANSFORMATIONS_FIELD_NUMBER
public static final int TRANSFORMATIONS_FIELD_NUMBER- See Also:
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OPTIMIZATION_OBJECTIVE_FIELD_NUMBER
public static final int OPTIMIZATION_OBJECTIVE_FIELD_NUMBER- See Also:
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TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER
public static final int TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER- See Also:
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WEIGHT_COLUMN_FIELD_NUMBER
public static final int WEIGHT_COLUMN_FIELD_NUMBER- See Also:
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TIME_SERIES_ATTRIBUTE_COLUMNS_FIELD_NUMBER
public static final int TIME_SERIES_ATTRIBUTE_COLUMNS_FIELD_NUMBER- See Also:
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UNAVAILABLE_AT_FORECAST_COLUMNS_FIELD_NUMBER
public static final int UNAVAILABLE_AT_FORECAST_COLUMNS_FIELD_NUMBER- See Also:
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AVAILABLE_AT_FORECAST_COLUMNS_FIELD_NUMBER
public static final int AVAILABLE_AT_FORECAST_COLUMNS_FIELD_NUMBER- See Also:
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DATA_GRANULARITY_FIELD_NUMBER
public static final int DATA_GRANULARITY_FIELD_NUMBER- See Also:
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FORECAST_HORIZON_FIELD_NUMBER
public static final int FORECAST_HORIZON_FIELD_NUMBER- See Also:
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CONTEXT_WINDOW_FIELD_NUMBER
public static final int CONTEXT_WINDOW_FIELD_NUMBER- See Also:
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EXPORT_EVALUATED_DATA_ITEMS_CONFIG_FIELD_NUMBER
public static final int EXPORT_EVALUATED_DATA_ITEMS_CONFIG_FIELD_NUMBER- See Also:
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QUANTILES_FIELD_NUMBER
public static final int QUANTILES_FIELD_NUMBER- See Also:
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VALIDATION_OPTIONS_FIELD_NUMBER
public static final int VALIDATION_OPTIONS_FIELD_NUMBER- See Also:
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ADDITIONAL_EXPERIMENTS_FIELD_NUMBER
public static final int ADDITIONAL_EXPERIMENTS_FIELD_NUMBER- See Also:
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Method Details
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getDescriptor
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() -
internalGetFieldAccessorTable
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()- Specified by:
internalGetFieldAccessorTablein classcom.google.protobuf.GeneratedMessage
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getTargetColumn
The name of the column that the model is to predict.
string target_column = 1;- Specified by:
getTargetColumnin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The targetColumn.
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getTargetColumnBytes
public com.google.protobuf.ByteString getTargetColumnBytes()The name of the column that the model is to predict.
string target_column = 1;- Specified by:
getTargetColumnBytesin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The bytes for targetColumn.
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getTimeSeriesIdentifierColumn
The name of the column that identifies the time series.
string time_series_identifier_column = 2;- Specified by:
getTimeSeriesIdentifierColumnin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The timeSeriesIdentifierColumn.
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getTimeSeriesIdentifierColumnBytes
public com.google.protobuf.ByteString getTimeSeriesIdentifierColumnBytes()The name of the column that identifies the time series.
string time_series_identifier_column = 2;- Specified by:
getTimeSeriesIdentifierColumnBytesin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The bytes for timeSeriesIdentifierColumn.
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getTimeColumn
The name of the column that identifies time order in the time series.
string time_column = 3;- Specified by:
getTimeColumnin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The timeColumn.
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getTimeColumnBytes
public com.google.protobuf.ByteString getTimeColumnBytes()The name of the column that identifies time order in the time series.
string time_column = 3;- Specified by:
getTimeColumnBytesin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The bytes for timeColumn.
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getTransformationsList
Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using "." as the delimiter.
repeated .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation transformations = 4;- Specified by:
getTransformationsListin interfaceAutoMlForecastingInputsOrBuilder
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getTransformationsOrBuilderList
public List<? extends AutoMlForecastingInputs.TransformationOrBuilder> getTransformationsOrBuilderList()Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using "." as the delimiter.
repeated .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation transformations = 4;- Specified by:
getTransformationsOrBuilderListin interfaceAutoMlForecastingInputsOrBuilder
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getTransformationsCount
public int getTransformationsCount()Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using "." as the delimiter.
repeated .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation transformations = 4;- Specified by:
getTransformationsCountin interfaceAutoMlForecastingInputsOrBuilder
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getTransformations
Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using "." as the delimiter.
repeated .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation transformations = 4;- Specified by:
getTransformationsin interfaceAutoMlForecastingInputsOrBuilder
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getTransformationsOrBuilder
Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using "." as the delimiter.
repeated .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation transformations = 4;- Specified by:
getTransformationsOrBuilderin interfaceAutoMlForecastingInputsOrBuilder
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getOptimizationObjective
Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * "minimize-rmse" (default) - Minimize root-mean-squared error (RMSE). * "minimize-mae" - Minimize mean-absolute error (MAE). * "minimize-rmsle" - Minimize root-mean-squared log error (RMSLE). * "minimize-rmspe" - Minimize root-mean-squared percentage error (RMSPE). * "minimize-wape-mae" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * "minimize-quantile-loss" - Minimize the quantile loss at the quantiles defined in `quantiles`.
string optimization_objective = 5;- Specified by:
getOptimizationObjectivein interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The optimizationObjective.
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getOptimizationObjectiveBytes
public com.google.protobuf.ByteString getOptimizationObjectiveBytes()Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * "minimize-rmse" (default) - Minimize root-mean-squared error (RMSE). * "minimize-mae" - Minimize mean-absolute error (MAE). * "minimize-rmsle" - Minimize root-mean-squared log error (RMSLE). * "minimize-rmspe" - Minimize root-mean-squared percentage error (RMSPE). * "minimize-wape-mae" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * "minimize-quantile-loss" - Minimize the quantile loss at the quantiles defined in `quantiles`.
string optimization_objective = 5;- Specified by:
getOptimizationObjectiveBytesin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The bytes for optimizationObjective.
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getTrainBudgetMilliNodeHours
public long getTrainBudgetMilliNodeHours()Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive.
int64 train_budget_milli_node_hours = 6;- Specified by:
getTrainBudgetMilliNodeHoursin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The trainBudgetMilliNodeHours.
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getWeightColumn
Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1.
string weight_column = 7;- Specified by:
getWeightColumnin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The weightColumn.
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getWeightColumnBytes
public com.google.protobuf.ByteString getWeightColumnBytes()Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1.
string weight_column = 7;- Specified by:
getWeightColumnBytesin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The bytes for weightColumn.
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getTimeSeriesAttributeColumnsList
public com.google.protobuf.ProtocolStringList getTimeSeriesAttributeColumnsList()Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.
repeated string time_series_attribute_columns = 19;- Specified by:
getTimeSeriesAttributeColumnsListin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- A list containing the timeSeriesAttributeColumns.
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getTimeSeriesAttributeColumnsCount
public int getTimeSeriesAttributeColumnsCount()Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.
repeated string time_series_attribute_columns = 19;- Specified by:
getTimeSeriesAttributeColumnsCountin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The count of timeSeriesAttributeColumns.
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getTimeSeriesAttributeColumns
Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.
repeated string time_series_attribute_columns = 19;- Specified by:
getTimeSeriesAttributeColumnsin interfaceAutoMlForecastingInputsOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The timeSeriesAttributeColumns at the given index.
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getTimeSeriesAttributeColumnsBytes
public com.google.protobuf.ByteString getTimeSeriesAttributeColumnsBytes(int index) Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.
repeated string time_series_attribute_columns = 19;- Specified by:
getTimeSeriesAttributeColumnsBytesin interfaceAutoMlForecastingInputsOrBuilder- Parameters:
index- The index of the value to return.- Returns:
- The bytes of the timeSeriesAttributeColumns at the given index.
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getAvailableAtForecastColumnsList
public com.google.protobuf.ProtocolStringList getAvailableAtForecastColumnsList()Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day.
repeated string available_at_forecast_columns = 21;- Specified by:
getAvailableAtForecastColumnsListin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- A list containing the availableAtForecastColumns.
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getAvailableAtForecastColumnsCount
public int getAvailableAtForecastColumnsCount()Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day.
repeated string available_at_forecast_columns = 21;- Specified by:
getAvailableAtForecastColumnsCountin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The count of availableAtForecastColumns.
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getAvailableAtForecastColumns
Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day.
repeated string available_at_forecast_columns = 21;- Specified by:
getAvailableAtForecastColumnsin interfaceAutoMlForecastingInputsOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The availableAtForecastColumns at the given index.
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getAvailableAtForecastColumnsBytes
public com.google.protobuf.ByteString getAvailableAtForecastColumnsBytes(int index) Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day.
repeated string available_at_forecast_columns = 21;- Specified by:
getAvailableAtForecastColumnsBytesin interfaceAutoMlForecastingInputsOrBuilder- Parameters:
index- The index of the value to return.- Returns:
- The bytes of the availableAtForecastColumns at the given index.
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hasDataGranularity
public boolean hasDataGranularity()Expected difference in time granularity between rows in the data.
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Granularity data_granularity = 22;- Specified by:
hasDataGranularityin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- Whether the dataGranularity field is set.
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getDataGranularity
Expected difference in time granularity between rows in the data.
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Granularity data_granularity = 22;- Specified by:
getDataGranularityin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The dataGranularity.
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getDataGranularityOrBuilder
Expected difference in time granularity between rows in the data.
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Granularity data_granularity = 22;- Specified by:
getDataGranularityOrBuilderin interfaceAutoMlForecastingInputsOrBuilder
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getForecastHorizon
public long getForecastHorizon()The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field.
int64 forecast_horizon = 23;- Specified by:
getForecastHorizonin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The forecastHorizon.
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getContextWindow
public long getContextWindow()The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field.
int64 context_window = 24;- Specified by:
getContextWindowin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The contextWindow.
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hasExportEvaluatedDataItemsConfig
public boolean hasExportEvaluatedDataItemsConfig()Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.ExportEvaluatedDataItemsConfig export_evaluated_data_items_config = 15;- Specified by:
hasExportEvaluatedDataItemsConfigin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- Whether the exportEvaluatedDataItemsConfig field is set.
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getExportEvaluatedDataItemsConfig
Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.ExportEvaluatedDataItemsConfig export_evaluated_data_items_config = 15;- Specified by:
getExportEvaluatedDataItemsConfigin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The exportEvaluatedDataItemsConfig.
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getExportEvaluatedDataItemsConfigOrBuilder
Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.ExportEvaluatedDataItemsConfig export_evaluated_data_items_config = 15;- Specified by:
getExportEvaluatedDataItemsConfigOrBuilderin interfaceAutoMlForecastingInputsOrBuilder
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getQuantilesList
Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique.
repeated double quantiles = 16;- Specified by:
getQuantilesListin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- A list containing the quantiles.
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getQuantilesCount
public int getQuantilesCount()Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique.
repeated double quantiles = 16;- Specified by:
getQuantilesCountin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The count of quantiles.
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getQuantiles
public double getQuantiles(int index) Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique.
repeated double quantiles = 16;- Specified by:
getQuantilesin interfaceAutoMlForecastingInputsOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The quantiles at the given index.
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getValidationOptions
Validation options for the data validation component. The available options are: * "fail-pipeline" - default, will validate against the validation and fail the pipeline if it fails. * "ignore-validation" - ignore the results of the validation and continue
string validation_options = 17;- Specified by:
getValidationOptionsin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The validationOptions.
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getValidationOptionsBytes
public com.google.protobuf.ByteString getValidationOptionsBytes()Validation options for the data validation component. The available options are: * "fail-pipeline" - default, will validate against the validation and fail the pipeline if it fails. * "ignore-validation" - ignore the results of the validation and continue
string validation_options = 17;- Specified by:
getValidationOptionsBytesin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The bytes for validationOptions.
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getAdditionalExperimentsList
public com.google.protobuf.ProtocolStringList getAdditionalExperimentsList()Additional experiment flags for the time series forcasting training.
repeated string additional_experiments = 25;- Specified by:
getAdditionalExperimentsListin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- A list containing the additionalExperiments.
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getAdditionalExperimentsCount
public int getAdditionalExperimentsCount()Additional experiment flags for the time series forcasting training.
repeated string additional_experiments = 25;- Specified by:
getAdditionalExperimentsCountin interfaceAutoMlForecastingInputsOrBuilder- Returns:
- The count of additionalExperiments.
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getAdditionalExperiments
Additional experiment flags for the time series forcasting training.
repeated string additional_experiments = 25;- Specified by:
getAdditionalExperimentsin interfaceAutoMlForecastingInputsOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The additionalExperiments at the given index.
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getAdditionalExperimentsBytes
public com.google.protobuf.ByteString getAdditionalExperimentsBytes(int index) Additional experiment flags for the time series forcasting training.
repeated string additional_experiments = 25;- Specified by:
getAdditionalExperimentsBytesin interfaceAutoMlForecastingInputsOrBuilder- Parameters:
index- The index of the value to return.- Returns:
- The bytes of the additionalExperiments at the given index.
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isInitialized
public final boolean isInitialized()- Specified by:
isInitializedin interfacecom.google.protobuf.MessageLiteOrBuilder- Overrides:
isInitializedin classcom.google.protobuf.GeneratedMessage
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writeTo
- Specified by:
writeToin interfacecom.google.protobuf.MessageLite- Overrides:
writeToin classcom.google.protobuf.GeneratedMessage- Throws:
IOException
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getSerializedSize
public int getSerializedSize()- Specified by:
getSerializedSizein interfacecom.google.protobuf.MessageLite- Overrides:
getSerializedSizein classcom.google.protobuf.GeneratedMessage
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equals
- Specified by:
equalsin interfacecom.google.protobuf.Message- Overrides:
equalsin classcom.google.protobuf.AbstractMessage
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hashCode
public int hashCode()- Specified by:
hashCodein interfacecom.google.protobuf.Message- Overrides:
hashCodein classcom.google.protobuf.AbstractMessage
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parseFrom
public static AutoMlForecastingInputs parseFrom(ByteBuffer data) throws com.google.protobuf.InvalidProtocolBufferException - Throws:
com.google.protobuf.InvalidProtocolBufferException
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parseFrom
public static AutoMlForecastingInputs parseFrom(ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException - Throws:
com.google.protobuf.InvalidProtocolBufferException
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parseFrom
public static AutoMlForecastingInputs parseFrom(com.google.protobuf.ByteString data) throws com.google.protobuf.InvalidProtocolBufferException - Throws:
com.google.protobuf.InvalidProtocolBufferException
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parseFrom
public static AutoMlForecastingInputs parseFrom(com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException - Throws:
com.google.protobuf.InvalidProtocolBufferException
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parseFrom
public static AutoMlForecastingInputs parseFrom(byte[] data) throws com.google.protobuf.InvalidProtocolBufferException - Throws:
com.google.protobuf.InvalidProtocolBufferException
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parseFrom
public static AutoMlForecastingInputs parseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException - Throws:
com.google.protobuf.InvalidProtocolBufferException
-
parseFrom
- Throws:
IOException
-
parseFrom
public static AutoMlForecastingInputs parseFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException - Throws:
IOException
-
parseDelimitedFrom
- Throws:
IOException
-
parseDelimitedFrom
public static AutoMlForecastingInputs parseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException - Throws:
IOException
-
parseFrom
public static AutoMlForecastingInputs parseFrom(com.google.protobuf.CodedInputStream input) throws IOException - Throws:
IOException
-
parseFrom
public static AutoMlForecastingInputs parseFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException - Throws:
IOException
-
newBuilderForType
- Specified by:
newBuilderForTypein interfacecom.google.protobuf.Message- Specified by:
newBuilderForTypein interfacecom.google.protobuf.MessageLite
-
newBuilder
-
newBuilder
-
toBuilder
- Specified by:
toBuilderin interfacecom.google.protobuf.Message- Specified by:
toBuilderin interfacecom.google.protobuf.MessageLite
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newBuilderForType
protected AutoMlForecastingInputs.Builder newBuilderForType(com.google.protobuf.AbstractMessage.BuilderParent parent) - Overrides:
newBuilderForTypein classcom.google.protobuf.AbstractMessage
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getDefaultInstance
-
parser
-
getParserForType
- Specified by:
getParserForTypein interfacecom.google.protobuf.Message- Specified by:
getParserForTypein interfacecom.google.protobuf.MessageLite- Overrides:
getParserForTypein classcom.google.protobuf.GeneratedMessage
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getDefaultInstanceForType
- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageLiteOrBuilder- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageOrBuilder
-