org.apache.spark.ml.feature

Interface StandardScalerParams

All Superinterfaces:

HasInputCol, HasOutputCol, Identifiable, Params, java.io.Serializable

All Known Implementing Classes:

StandardScaler, StandardScalerModel

public interface StandardScalerParams
extends Params, HasInputCol, HasOutputCol

Params for StandardScaler and StandardScalerModel.

Method Summary

Modifier and Type	Method and Description
boolean	getWithMean()
boolean	getWithStd()
StructType	validateAndTransformSchema(StructType schema) Validates and transforms the input schema.
BooleanParam	withMean() Whether to center the data with mean before scaling.
BooleanParam	withStd() Whether to scale the data to unit standard deviation.

Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCol

getInputCol, inputCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCol

getOutputCol, outputCol

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString, uid

Method Detail

getWithMean

boolean getWithMean()

getWithStd

boolean getWithStd()

validateAndTransformSchema

StructType validateAndTransformSchema(StructType schema)

Validates and transforms the input schema.

withMean

BooleanParam withMean()

Whether to center the data with mean before scaling. It will build a dense output, so take care when applying to sparse input. Default: false

Returns:

(undocumented)

withStd

BooleanParam withStd()

Whether to scale the data to unit standard deviation. Default: true

Returns:

(undocumented)