org.apache.spark.ml.feature

Class MinMaxScaler

Object

org.apache.spark.ml.PipelineStage

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

org.apache.spark.ml.feature.MinMaxScaler

All Implemented Interfaces:

java.io.Serializable, Params, DefaultParamsWritable, Identifiable, MLWritable

public class MinMaxScaler
extends Estimator<MinMaxScalerModel>
implements DefaultParamsWritable

Rescale each feature individually to a common range [min, max] linearly using column summary statistics, which is also known as min-max normalization or Rescaling. The rescaled value for feature E is calculated as:

$$ Rescaled(e_i) = \frac{e_i - E_{min}}{E_{max} - E_{min}} * (max - min) + min $$

For the case $E_{max} == E_{min}$, $Rescaled(e_i) = 0.5 * (max + min)$.

See Also:

Serialized Form

Note:

Since zero values will probably be transformed to non-zero values, output of the transformer will be DenseVector even for sparse input.

Constructor Summary

Constructors

Constructor and Description
MinMaxScaler()
MinMaxScaler(String uid)

Method Summary

Methods

Modifier and Type	Method and Description
static Params	clear(Param<?> param)
MinMaxScaler	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)
MinMaxScalerModel	fit(Dataset<?> dataset) Fits a model to the input data.
static <T> scala.Option<T>	get(Param<T> param)
static <T> scala.Option<T>	getDefault(Param<T> param)
static String	getInputCol()
static double	getMax()
double	getMax()
static double	getMin()
double	getMin()
static <T> T	getOrDefault(Param<T> param)
static String	getOutputCol()
static Param<Object>	getParam(String paramName)
static <T> boolean	hasDefault(Param<T> param)
static boolean	hasParam(String paramName)
static Param<String>	inputCol()
static boolean	isDefined(Param<?> param)
static boolean	isSet(Param<?> param)
static MinMaxScaler	load(String path)
static DoubleParam	max()
DoubleParam	max() upper bound after transformation, shared by all features Default: 1.0
static DoubleParam	min()
DoubleParam	min() lower bound after transformation, shared by all features Default: 0.0
static Param<String>	outputCol()
static Param<?>[]	params()
static void	save(String path)
static <T> Params	set(Param<T> param, T value)
MinMaxScaler	setInputCol(String value)
MinMaxScaler	setMax(double value)
MinMaxScaler	setMin(double value)
MinMaxScaler	setOutputCol(String value)
static String	toString()
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 MLWriter	write()

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

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, 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

Constructor Detail

MinMaxScaler

public MinMaxScaler(String uid)

MinMaxScaler

public MinMaxScaler()

Method Detail

load

public static MinMaxScaler load(String path)

toString

public static String toString()

params

public static Param<?>[] params()

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()

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()

min

public static DoubleParam min()

getMin

public static double getMin()

max

public static DoubleParam max()

getMax

public static double getMax()

save

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

Throws:

java.io.IOException

write

public static MLWriter write()

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 MinMaxScaler setInputCol(String value)

setOutputCol

public MinMaxScaler setOutputCol(String value)

setMin

public MinMaxScaler setMin(double value)

setMax

public MinMaxScaler setMax(double value)

fit

public MinMaxScalerModel fit(Dataset<?> dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<MinMaxScalerModel>

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.

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 MinMaxScaler 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<MinMaxScalerModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

min

public DoubleParam min()

lower bound after transformation, shared by all features Default: 0.0

Returns:

(undocumented)

getMin

public double getMin()

max

public DoubleParam max()

upper bound after transformation, shared by all features Default: 1.0

Returns:

(undocumented)

getMax

public double getMax()

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema)

Validates and transforms the input schema.