ValueIndexerModel

class ValueIndexerModel.ValueIndexerModel(dataType='string', inputCol='input', levels=None, outputCol=None)[source]

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

Model produced by ValueIndexer.

Parameters:
  • dataType (str) – The datatype of the levels as a Json string (default: string)
  • inputCol (str) – The name of the input column (default: input)
  • levels (object) – Levels in categorical array
  • outputCol (str) – The name of the output column (default: [self.uid]_output)
getDataType()[source]
Returns:The datatype of the levels as a Json string (default: string)
Return type:str
getInputCol()[source]
Returns:The name of the input column (default: input)
Return type:str
static getJavaPackage()[source]

Returns package name String.

getLevels()[source]
Returns:Levels in categorical array
Return type:object
getOutputCol()[source]
Returns:The name of the output column (default: [self.uid]_output)
Return type:str
classmethod read()[source]

Returns an MLReader instance for this class.

setDataType(value)[source]
Parameters:dataType (str) – The datatype of the levels as a Json string (default: string)
setInputCol(value)[source]
Parameters:inputCol (str) – The name of the input column (default: input)
setLevels(value)[source]
Parameters:levels (object) – Levels in categorical array
setOutputCol(value)[source]
Parameters:outputCol (str) – The name of the output column (default: [self.uid]_output)
setParams(dataType='string', inputCol='input', levels=None, outputCol=None)[source]

Set the (keyword only) parameters

Parameters:
  • dataType (str) – The datatype of the levels as a Json string (default: string)
  • inputCol (str) – The name of the input column (default: input)
  • levels (object) – Levels in categorical array
  • outputCol (str) – The name of the output column (default: [self.uid]_output)