org.apache.spark.ml.regression

Class IsotonicRegression

Object

org.apache.spark.ml.PipelineStage

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

org.apache.spark.ml.regression.IsotonicRegression

All Implemented Interfaces:

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

public class IsotonicRegression
extends Estimator<IsotonicRegressionModel>
implements DefaultParamsWritable

Isotonic regression.

Currently implemented using parallelized pool adjacent violators algorithm. Only univariate (single feature) algorithm supported.

Uses IsotonicRegression.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
IsotonicRegression()
IsotonicRegression(String uid)

Method Summary

Modifier and Type	Method and Description
static Params	clear(Param<?> param)
IsotonicRegression	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)
RDD<scala.Tuple3<Object,Object,Object>>	extractWeightedLabeledPoints(Dataset<?> dataset) Extracts (label, feature, weight) from input dataset.
static IntParam	featureIndex()
IntParam	featureIndex() Param for the index of the feature if featuresCol is a vector column (default: 0), no effect otherwise.
static Param<String>	featuresCol()
IsotonicRegressionModel	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 int	getFeatureIndex()
int	getFeatureIndex()
static String	getFeaturesCol()
static boolean	getIsotonic()
boolean	getIsotonic()
static String	getLabelCol()
static <T> T	getOrDefault(Param<T> param)
static Param<Object>	getParam(String paramName)
static String	getPredictionCol()
static String	getWeightCol()
static <T> boolean	hasDefault(Param<T> param)
static boolean	hasParam(String paramName)
boolean	hasWeightCol() Checks whether the input has weight column.
static boolean	isDefined(Param<?> param)
static BooleanParam	isotonic()
BooleanParam	isotonic() Param for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false).
static boolean	isSet(Param<?> param)
static Param<String>	labelCol()
static IsotonicRegression	load(String path)
static Param<?>[]	params()
static Param<String>	predictionCol()
static void	save(String path)
static <T> Params	set(Param<T> param, T value)
IsotonicRegression	setFeatureIndex(int value)
IsotonicRegression	setFeaturesCol(String value)
IsotonicRegression	setIsotonic(boolean value)
IsotonicRegression	setLabelCol(String value)
IsotonicRegression	setPredictionCol(String value)
IsotonicRegression	setWeightCol(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, boolean fitting) Validates and transforms input schema.
static Param<String>	weightCol()
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.shared.HasFeaturesCol

featuresCol, getFeaturesCol

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

getLabelCol, labelCol

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

getPredictionCol, predictionCol

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

getWeightCol, weightCol

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.internal.Logging

initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

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

write

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

save

Constructor Detail

IsotonicRegression

public IsotonicRegression(String uid)

IsotonicRegression

public IsotonicRegression()

Method Detail

load

public static IsotonicRegression 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()

featuresCol

public static final Param<String> featuresCol()

getFeaturesCol

public static final String getFeaturesCol()

labelCol

public static final Param<String> labelCol()

getLabelCol

public static final String getLabelCol()

predictionCol

public static final Param<String> predictionCol()

getPredictionCol

public static final String getPredictionCol()

weightCol

public static final Param<String> weightCol()

getWeightCol

public static final String getWeightCol()

isotonic

public static final BooleanParam isotonic()

getIsotonic

public static final boolean getIsotonic()

featureIndex

public static final IntParam featureIndex()

getFeatureIndex

public static final int getFeatureIndex()

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)

setLabelCol

public IsotonicRegression setLabelCol(String value)

setFeaturesCol

public IsotonicRegression setFeaturesCol(String value)

setPredictionCol

public IsotonicRegression setPredictionCol(String value)

setIsotonic

public IsotonicRegression setIsotonic(boolean value)

setWeightCol

public IsotonicRegression setWeightCol(String value)

setFeatureIndex

public IsotonicRegression setFeatureIndex(int value)

copy

public IsotonicRegression 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<IsotonicRegressionModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

fit

public IsotonicRegressionModel fit(Dataset<?> dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<IsotonicRegressionModel>

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)

extractWeightedLabeledPoints

public RDD<scala.Tuple3<Object,Object,Object>> extractWeightedLabeledPoints(Dataset<?> dataset)

Extracts (label, feature, weight) from input dataset.

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

featureIndex

public IntParam featureIndex()

Param for the index of the feature if featuresCol is a vector column (default: 0), no effect otherwise.

Returns:

(undocumented)

getFeatureIndex

public int getFeatureIndex()

getIsotonic

public boolean getIsotonic()

hasWeightCol

public boolean hasWeightCol()

Checks whether the input has weight column.

isotonic

public BooleanParam isotonic()

Param for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false). Default: true

Returns:

(undocumented)

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema,
                                             boolean fitting)

Validates and transforms input schema.

Parameters:

schema - input schema

fitting - whether this is in fitting or prediction

Returns:

output schema