org.apache.spark.ml.feature
Class StandardScalerModel

Object
  org.apache.spark.ml.PipelineStage
      org.apache.spark.ml.Transformer
          org.apache.spark.ml.Model<StandardScalerModel>
              org.apache.spark.ml.feature.StandardScalerModel

All Implemented Interfaces:

java.io.Serializable, Logging, Params

public class StandardScalerModel
extends Model<StandardScalerModel>

See Also:

Serialized Form

Method Summary

StandardScalerModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
StandardScalerModel	setInputCol(String value)
StandardScalerModel	setOutputCol(String value)
DataFrame	transform(DataFrame dataset) Transforms the input dataset.
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.Model

hasParent, parent, setParent

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

transform, transform, transform

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, copyValues, defaultCopy, 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

Method Detail

uid

public String uid()

setInputCol

public StandardScalerModel setInputCol(String value)

setOutputCol

public StandardScalerModel setOutputCol(String value)

transform

public DataFrame transform(DataFrame dataset)

Description copied from class: Transformer

Transforms the input dataset.

Specified by:

transform in class Transformer

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)

copy

public StandardScalerModel copy(ParamMap extra)

Description copied from interface: Params

Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly.

Specified by:

copy in interface Params

Specified by:

copy in class Model<StandardScalerModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()

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)