org.apache.spark.ml.feature

Class MaxAbsScaler

Object

org.apache.spark.ml.PipelineStage

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

org.apache.spark.ml.feature.MaxAbsScaler

All Implemented Interfaces:

java.io.Serializable, org.apache.spark.internal.Logging, MaxAbsScalerParams, Params, HasInputCol, HasOutputCol, DefaultParamsWritable, Identifiable, MLWritable

public class MaxAbsScaler
extends Estimator<MaxAbsScalerModel>
implements MaxAbsScalerParams, DefaultParamsWritable

Rescale each feature individually to range [-1, 1] by dividing through the largest maximum absolute value in each feature. It does not shift/center the data, and thus does not destroy any sparsity.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
MaxAbsScaler()
MaxAbsScaler(String uid)

Method Summary

Modifier and Type	Method and Description
MaxAbsScaler	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
MaxAbsScalerModel	fit(Dataset<?> dataset) Fits a model to the input data.
Param<String>	inputCol() Param for input column name.
static MaxAbsScaler	load(String path)
Param<String>	outputCol() Param for output column name.
static MLReader<T>	read()
MaxAbsScaler	setInputCol(String value)
MaxAbsScaler	setOutputCol(String value)
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.

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

fit, fit, fit, fit

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

params

Methods inherited from class Object

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

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

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

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

toString

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

write

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

Constructor Detail

MaxAbsScaler

public MaxAbsScaler(String uid)

MaxAbsScaler

public MaxAbsScaler()

Method Detail

load

public static MaxAbsScaler load(String path)

read

public static MLReader<T> read()

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)

setInputCol

public MaxAbsScaler setInputCol(String value)

setOutputCol

public MaxAbsScaler setOutputCol(String value)

fit

public MaxAbsScalerModel fit(Dataset<?> dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<MaxAbsScalerModel>

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 MaxAbsScaler 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 Estimator<MaxAbsScalerModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)