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, Params, Identifiable, MLWritable

public class StandardScalerModel
extends Model<StandardScalerModel>
implements MLWritable

Model fitted by StandardScaler.

param: std Standard deviation of the StandardScalerModel param: mean Mean of the StandardScalerModel

See Also:

Serialized Form

Method Summary

Methods

Modifier and Type	Method and Description
static Params	clear(Param<?> param)
StandardScalerModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
static String	explainParam(Param<?> param)
static String	explainParams()
static ParamMap	extractParamMap()
static ParamMap	extractParamMap(ParamMap extra)
static <T> scala.Option<T>	get(Param<T> param)
static <T> scala.Option<T>	getDefault(Param<T> param)
static String	getInputCol()
static <T> T	getOrDefault(Param<T> param)
static String	getOutputCol()
static Param<Object>	getParam(String paramName)
static boolean	getWithMean()
boolean	getWithMean()
static boolean	getWithStd()
boolean	getWithStd()
static <T> boolean	hasDefault(Param<T> param)
static boolean	hasParam(String paramName)
static boolean	hasParent()
static Param<String>	inputCol()
static boolean	isDefined(Param<?> param)
static boolean	isSet(Param<?> param)
static StandardScalerModel	load(String path)
Vector	mean()
static Param<String>	outputCol()
static Param<?>[]	params()
static void	parent_$eq(Estimator<M> x$1)
static Estimator<M>	parent()
static MLReader<StandardScalerModel>	read()
static void	save(String path)
static <T> Params	set(Param<T> param, T value)
StandardScalerModel	setInputCol(String value)
StandardScalerModel	setOutputCol(String value)
static M	setParent(Estimator<M> parent)
Vector	std()
static String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
String	uid() An immutable unique ID for the object and its derivatives.
StructType	validateAndTransformSchema(StructType schema) Validates and transforms the input schema.
static void	validateParams()
static BooleanParam	withMean()
BooleanParam	withMean() Whether to center the data with mean before scaling.
static BooleanParam	withStd()
BooleanParam	withStd() Whether to scale the data to unit standard deviation.
MLWriter	write() Returns an MLWriter instance for this ML instance.

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, shouldOwn, validateParams

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

toString

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

save

Method Detail

read

public static MLReader<StandardScalerModel> read()

load

public static StandardScalerModel load(String path)

toString

public static String toString()

params

public static Param<?>[] params()

validateParams

public static void validateParams()

explainParam

public static String explainParam(Param<?> param)

explainParams

public static String explainParams()

isSet

public static final boolean isSet(Param<?> param)

isDefined

public static final boolean isDefined(Param<?> param)

hasParam

public static boolean hasParam(String paramName)

getParam

public static Param<Object> getParam(String paramName)

set

public static final <T> Params set(Param<T> param,
             T value)

get

public static final <T> scala.Option<T> get(Param<T> param)

clear

public static final Params clear(Param<?> param)

getOrDefault

public static final <T> T getOrDefault(Param<T> param)

getDefault

public static final <T> scala.Option<T> getDefault(Param<T> param)

hasDefault

public static final <T> boolean hasDefault(Param<T> param)

extractParamMap

public static final ParamMap extractParamMap(ParamMap extra)

extractParamMap

public static final ParamMap extractParamMap()

parent

public static Estimator<M> parent()

parent_$eq

public static void parent_$eq(Estimator<M> x$1)

setParent

public static M setParent(Estimator<M> parent)

hasParent

public static boolean hasParent()

inputCol

public static final Param<String> inputCol()

getInputCol

public static final String getInputCol()

outputCol

public static final Param<String> outputCol()

getOutputCol

public static final String getOutputCol()

withMean

public static BooleanParam withMean()

getWithMean

public static boolean getWithMean()

withStd

public static BooleanParam withStd()

getWithStd

public static boolean getWithStd()

save

public static void save(String path)
                 throws java.io.IOException

Throws:

java.io.IOException

uid

public String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

std

public Vector std()

mean

public Vector mean()

setInputCol

public StandardScalerModel setInputCol(String value)

setOutputCol

public StandardScalerModel setOutputCol(String value)

transform

public Dataset<Row> transform(Dataset<?> 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 ::

Check transform validity and derive the output schema from the input schema.

Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.

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. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Model<StandardScalerModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

write

public MLWriter write()

Description copied from interface: MLWritable

Returns an MLWriter instance for this ML instance.

Specified by:

write in interface MLWritable

Returns:

(undocumented)

withMean

public BooleanParam withMean()

Whether to center 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)

getWithMean

public boolean getWithMean()

withStd

public BooleanParam withStd()

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

Returns:

(undocumented)

getWithStd

public boolean getWithStd()

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema)

Validates and transforms the input schema.