MultiColumnAdapter

class MultiColumnAdapter.MultiColumnAdapter(baseStage=None, inputCols=None, outputCols=None)

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

Takes a unary pipeline stage and a list of input/output column pairs and applies the pipeline stage to each column after a fit

Parameters:

• baseStage (object) – base pipeline stage to apply to every column
• inputCols (list) – list of column names encoded as a string
• outputCols (list) – list of column names encoded as a string

getBaseStage()

Returns:base pipeline stage to apply to every column Return type:object

getInputCols()

Returns:list of column names encoded as a string Return type:list

static getJavaPackage()

Returns package name String.

getOutputCols()

Returns:list of column names encoded as a string Return type:list

classmethod read()

Returns an MLReader instance for this class.

setBaseStage(value)

Parameters:baseStage (object) – base pipeline stage to apply to every column

setInputCols(value)

Parameters:inputCols (list) – list of column names encoded as a string

setOutputCols(value)

Parameters:outputCols (list) – list of column names encoded as a string

setParams(baseStage=None, inputCols=None, outputCols=None)

Set the (keyword only) parameters

Parameters:

• baseStage (object) – base pipeline stage to apply to every column
• inputCols (list) – list of column names encoded as a string
• outputCols (list) – list of column names encoded as a string

class MultiColumnAdapter.PipelineModel(java_model=None)

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

Model fitted by MultiColumnAdapter.

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

static getJavaPackage()

Returns package name String.

classmethod read()

Returns an MLReader instance for this class.