org.apache.spark.ml.feature

Class StandardScaler

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Estimator<StandardScalerModel>

org.apache.spark.ml.feature.StandardScaler

All Implemented Interfaces:

java.io.Serializable, Logging, Params

public class StandardScaler
extends Estimator<StandardScalerModel>

:: Experimental :: Standardizes features by removing the mean and scaling to unit variance using column summary statistics on the samples in the training set.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
StandardScaler()
StandardScaler(String uid)

Method Summary

Methods

Modifier and Type	Method and Description
StandardScalerModel	fit(DataFrame dataset) Fits a model to the input data.
StandardScaler	setInputCol(String value)
StandardScaler	setOutputCol(String value)
StandardScaler	setWithMean(boolean value)
StandardScaler	setWithStd(boolean value)
StructType	transformSchema(StructType schema) :: DeveloperApi ::
String	uid()
BooleanParam	withMean() Centers the data with mean before scaling.
BooleanParam	withStd() Scales the data to unit standard deviation.

Methods inherited from class org.apache.spark.ml.Estimator

copy, fit, fit, fit, fit

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

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

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

Methods inherited from interface org.apache.spark.Logging

initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

StandardScaler

public StandardScaler(String uid)

StandardScaler

public StandardScaler()

Method Detail

uid

public String uid()

setInputCol

public StandardScaler setInputCol(String value)

setOutputCol

public StandardScaler setOutputCol(String value)

setWithMean

public StandardScaler setWithMean(boolean value)

setWithStd

public StandardScaler setWithStd(boolean value)

fit

public StandardScalerModel fit(DataFrame dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<StandardScalerModel>

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

Derives the output schema from the input schema.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

withMean

public BooleanParam withMean()

Centers the data with mean before scaling. It will build a dense output, so this does not work on sparse input and will raise an exception. Default: false

Returns:

(undocumented)

withStd

public BooleanParam withStd()

Scales the data to unit standard deviation. Default: true

Returns:

(undocumented)