Class TableVerticalFeaturizationSettings
- java.lang.Object
-
- com.azure.resourcemanager.machinelearning.models.FeaturizationSettings
-
- com.azure.resourcemanager.machinelearning.models.TableVerticalFeaturizationSettings
-
public final class TableVerticalFeaturizationSettings extends FeaturizationSettings
Featurization Configuration.
-
-
Constructor Summary
Constructors Constructor Description TableVerticalFeaturizationSettings()
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description List<String>
blockedTransformers()
Get the blockedTransformers property: These transformers shall not be used in featurization.Map<String,String>
columnNameAndTypes()
Get the columnNameAndTypes property: Dictionary of column name and its type (int, float, string, datetime etc).List<String>
dropColumns()
Get the dropColumns property: Columns to be dropped from data during featurization.Boolean
enableDnnFeaturization()
Get the enableDnnFeaturization property: Determines whether to use Dnn based featurizers for data featurization.FeaturizationMode
mode()
Get the mode property: Featurization mode - User can keep the default 'Auto' mode and AutoML will take care of necessary transformation of the data in featurization phase.Map<String,List<ColumnTransformer>>
transformerParams()
Get the transformerParams property: User can specify additional transformers to be used along with the columns to which it would be applied and parameters for the transformer constructor.void
validate()
Validates the instance.TableVerticalFeaturizationSettings
withBlockedTransformers(List<String> blockedTransformers)
Set the blockedTransformers property: These transformers shall not be used in featurization.TableVerticalFeaturizationSettings
withColumnNameAndTypes(Map<String,String> columnNameAndTypes)
Set the columnNameAndTypes property: Dictionary of column name and its type (int, float, string, datetime etc).TableVerticalFeaturizationSettings
withDatasetLanguage(String datasetLanguage)
Set the datasetLanguage property: Dataset language, useful for the text data.TableVerticalFeaturizationSettings
withDropColumns(List<String> dropColumns)
Set the dropColumns property: Columns to be dropped from data during featurization.TableVerticalFeaturizationSettings
withEnableDnnFeaturization(Boolean enableDnnFeaturization)
Set the enableDnnFeaturization property: Determines whether to use Dnn based featurizers for data featurization.TableVerticalFeaturizationSettings
withMode(FeaturizationMode mode)
Set the mode property: Featurization mode - User can keep the default 'Auto' mode and AutoML will take care of necessary transformation of the data in featurization phase.TableVerticalFeaturizationSettings
withTransformerParams(Map<String,List<ColumnTransformer>> transformerParams)
Set the transformerParams property: User can specify additional transformers to be used along with the columns to which it would be applied and parameters for the transformer constructor.-
Methods inherited from class com.azure.resourcemanager.machinelearning.models.FeaturizationSettings
datasetLanguage
-
-
-
-
Method Detail
-
blockedTransformers
public List<String> blockedTransformers()
Get the blockedTransformers property: These transformers shall not be used in featurization.- Returns:
- the blockedTransformers value.
-
withBlockedTransformers
public TableVerticalFeaturizationSettings withBlockedTransformers(List<String> blockedTransformers)
Set the blockedTransformers property: These transformers shall not be used in featurization.- Parameters:
blockedTransformers
- the blockedTransformers value to set.- Returns:
- the TableVerticalFeaturizationSettings object itself.
-
columnNameAndTypes
public Map<String,String> columnNameAndTypes()
Get the columnNameAndTypes property: Dictionary of column name and its type (int, float, string, datetime etc).- Returns:
- the columnNameAndTypes value.
-
withColumnNameAndTypes
public TableVerticalFeaturizationSettings withColumnNameAndTypes(Map<String,String> columnNameAndTypes)
Set the columnNameAndTypes property: Dictionary of column name and its type (int, float, string, datetime etc).- Parameters:
columnNameAndTypes
- the columnNameAndTypes value to set.- Returns:
- the TableVerticalFeaturizationSettings object itself.
-
dropColumns
public List<String> dropColumns()
Get the dropColumns property: Columns to be dropped from data during featurization.- Returns:
- the dropColumns value.
-
withDropColumns
public TableVerticalFeaturizationSettings withDropColumns(List<String> dropColumns)
Set the dropColumns property: Columns to be dropped from data during featurization.- Parameters:
dropColumns
- the dropColumns value to set.- Returns:
- the TableVerticalFeaturizationSettings object itself.
-
enableDnnFeaturization
public Boolean enableDnnFeaturization()
Get the enableDnnFeaturization property: Determines whether to use Dnn based featurizers for data featurization.- Returns:
- the enableDnnFeaturization value.
-
withEnableDnnFeaturization
public TableVerticalFeaturizationSettings withEnableDnnFeaturization(Boolean enableDnnFeaturization)
Set the enableDnnFeaturization property: Determines whether to use Dnn based featurizers for data featurization.- Parameters:
enableDnnFeaturization
- the enableDnnFeaturization value to set.- Returns:
- the TableVerticalFeaturizationSettings object itself.
-
mode
public FeaturizationMode mode()
Get the mode property: Featurization mode - User can keep the default 'Auto' mode and AutoML will take care of necessary transformation of the data in featurization phase. If 'Off' is selected then no featurization is done. If 'Custom' is selected then user can specify additional inputs to customize how featurization is done.- Returns:
- the mode value.
-
withMode
public TableVerticalFeaturizationSettings withMode(FeaturizationMode mode)
Set the mode property: Featurization mode - User can keep the default 'Auto' mode and AutoML will take care of necessary transformation of the data in featurization phase. If 'Off' is selected then no featurization is done. If 'Custom' is selected then user can specify additional inputs to customize how featurization is done.- Parameters:
mode
- the mode value to set.- Returns:
- the TableVerticalFeaturizationSettings object itself.
-
transformerParams
public Map<String,List<ColumnTransformer>> transformerParams()
Get the transformerParams property: User can specify additional transformers to be used along with the columns to which it would be applied and parameters for the transformer constructor.- Returns:
- the transformerParams value.
-
withTransformerParams
public TableVerticalFeaturizationSettings withTransformerParams(Map<String,List<ColumnTransformer>> transformerParams)
Set the transformerParams property: User can specify additional transformers to be used along with the columns to which it would be applied and parameters for the transformer constructor.- Parameters:
transformerParams
- the transformerParams value to set.- Returns:
- the TableVerticalFeaturizationSettings object itself.
-
withDatasetLanguage
public TableVerticalFeaturizationSettings withDatasetLanguage(String datasetLanguage)
Set the datasetLanguage property: Dataset language, useful for the text data.- Overrides:
withDatasetLanguage
in classFeaturizationSettings
- Parameters:
datasetLanguage
- the datasetLanguage value to set.- Returns:
- the FeaturizationSettings object itself.
-
validate
public void validate()
Validates the instance.- Overrides:
validate
in classFeaturizationSettings
- Throws:
IllegalArgumentException
- thrown if the instance is not valid.
-
-