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, org.apache.spark.internal.Logging, StandardScalerParams, Params, HasInputCol, HasOutputCol, Identifiable, MLWritable

public class StandardScalerModel
extends Model<StandardScalerModel>
implements StandardScalerParams, MLWritable

Model fitted by StandardScaler.

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

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.SparkShellLoggingFilter

Method Summary

Modifier and Type	Method and Description
StandardScalerModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
Param<String>	inputCol() Param for input column name.
static StandardScalerModel	load(String path)
Vector	mean()
Param<String>	outputCol() Param for output column name.
static MLReader<StandardScalerModel>	read()
StandardScalerModel	setInputCol(String value)
StandardScalerModel	setOutputCol(String value)
Vector	std()
String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) Check transform validity and derive the output schema from the input schema.
String	uid() An immutable unique ID for the object and its derivatives.
BooleanParam	withMean() Whether to center the data with mean before scaling.
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 org.apache.spark.ml.PipelineStage

params

Methods inherited from class Object

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

Methods inherited from interface org.apache.spark.ml.feature.StandardScalerParams

getWithMean, getWithStd, validateAndTransformSchema

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

getInputCol

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

getOutputCol

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, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

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

save

Methods inherited from interface org.apache.spark.internal.Logging

$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize

Method Detail

read

public static MLReader<StandardScalerModel> read()

load

public static StandardScalerModel load(String path)

withMean

public BooleanParam withMean()

Description copied from interface: StandardScalerParams

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

Specified by:

withMean in interface StandardScalerParams

Returns:

(undocumented)

withStd

public BooleanParam withStd()

Description copied from interface: StandardScalerParams

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

Specified by:

withStd in interface StandardScalerParams

Returns:

(undocumented)

outputCol

public final Param<String> outputCol()

Description copied from interface: HasOutputCol

Param for output column name.

Specified by:

outputCol in interface HasOutputCol

Returns:

(undocumented)

inputCol

public final Param<String> inputCol()

Description copied from interface: HasInputCol

Param for input column name.

Specified by:

inputCol in interface HasInputCol

Returns:

(undocumented)

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

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

We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().

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)

toString

public String toString()

Specified by:

toString in interface Identifiable

Overrides:

toString in class Object