AssembleFeatures¶

class AssembleFeatures.AssembleFeatures(allowImages=False, columnsToFeaturize=None, featuresCol='features', numberOfFeatures=None, oneHotEncodeCategoricals=True)[source]¶

Bases: mmlspark.Utils.ComplexParamsMixin, pyspark.ml.util.JavaMLReadable, pyspark.ml.util.JavaMLWritable, pyspark.ml.wrapper.JavaEstimator

Assembles feature columns into a vector column of features.

Parameters:	allowImages (bool) – Allow featurization of images (default: false) columnsToFeaturize (list) – Columns to featurize featuresCol (str) – The name of the features column (default: features) numberOfFeatures (int) – Number of features to hash string columns to oneHotEncodeCategoricals (bool) – One-hot encode categoricals (default: true)

getAllowImages()[source]¶

Returns:	Allow featurization of images (default: false)
Return type:	bool

getColumnsToFeaturize()[source]¶

Returns:	Columns to featurize
Return type:	list

getFeaturesCol()[source]¶

Returns:	The name of the features column (default: features)
Return type:	str

static getJavaPackage()[source]¶: Returns package name String.

getNumberOfFeatures()[source]¶

Returns:	Number of features to hash string columns to
Return type:	int

getOneHotEncodeCategoricals()[source]¶

Returns:	One-hot encode categoricals (default: true)
Return type:	bool

classmethod read()[source]¶: Returns an MLReader instance for this class.

setAllowImages(value)[source]¶

Parameters:	allowImages (bool) – Allow featurization of images (default: false)

setColumnsToFeaturize(value)[source]¶

Parameters:	columnsToFeaturize (list) – Columns to featurize

setFeaturesCol(value)[source]¶

Parameters:	featuresCol (str) – The name of the features column (default: features)

setNumberOfFeatures(value)[source]¶

Parameters:	numberOfFeatures (int) – Number of features to hash string columns to

setOneHotEncodeCategoricals(value)[source]¶

Parameters:	oneHotEncodeCategoricals (bool) – One-hot encode categoricals (default: true)

setParams(allowImages=False, columnsToFeaturize=None, featuresCol='features', numberOfFeatures=None, oneHotEncodeCategoricals=True)[source]¶

Set the (keyword only) parameters

Parameters:	allowImages (bool) – Allow featurization of images (default: false) columnsToFeaturize (list) – Columns to featurize featuresCol (str) – The name of the features column (default: features) numberOfFeatures (int) – Number of features to hash string columns to oneHotEncodeCategoricals (bool) – One-hot encode categoricals (default: true)

class AssembleFeatures.AssembleFeaturesModel(java_model=None)[source]¶

Bases: mmlspark.Utils.ComplexParamsMixin, pyspark.ml.wrapper.JavaModel, pyspark.ml.util.JavaMLWritable, pyspark.ml.util.JavaMLReadable

Model fitted by AssembleFeatures.

This class is left empty on purpose. All necessary methods are exposed through inheritance.

static getJavaPackage()[source]¶: Returns package name String.

classmethod read()[source]¶: Returns an MLReader instance for this class.