org.apache.spark.ml.regression

Class IsotonicRegression

java.lang.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, Identifiable

public class IsotonicRegression
extends Estimator<IsotonicRegressionModel>

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
IsotonicRegression()
IsotonicRegression(java.lang.String uid)

Method Summary

Methods

Modifier and Type	Method and Description
IsotonicRegression	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
RDD<scala.Tuple3<java.lang.Object,java.lang.Object,java.lang.Object>>	extractWeightedLabeledPoints(DataFrame dataset) Extracts (label, feature, weight) from input dataset.
IntParam	featureIndex() Param for the index of the feature if featuresCol is a vector column (default: 0), no effect otherwise.
IsotonicRegressionModel	fit(DataFrame dataset) Fits a model to the input data.
int	getFeatureIndex()
boolean	getIsotonic()
boolean	hasWeightCol() Checks whether the input has weight column.
BooleanParam	isotonic() Param for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false).
static IsotonicRegression	load(java.lang.String path)
IsotonicRegression	setFeatureIndex(int value)
IsotonicRegression	setFeaturesCol(java.lang.String value)
IsotonicRegression	setIsotonic(boolean value)
IsotonicRegression	setLabelCol(java.lang.String value)
IsotonicRegression	setPredictionCol(java.lang.String value)
IsotonicRegression	setWeightCol(java.lang.String value)
StructType	transformSchema(StructType schema) :: DeveloperApi ::
java.lang.String	uid() An immutable unique ID for the object and its derivatives.
StructType	validateAndTransformSchema(StructType schema, boolean fitting)

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

fit, fit, fit, fit

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

transformSchema

Methods inherited from class java.lang.Object

clone, equals, finalize, 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.Logging

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

Constructor Detail

IsotonicRegression

public IsotonicRegression(java.lang.String uid)

IsotonicRegression

public IsotonicRegression()

Method Detail

load

public static IsotonicRegression load(java.lang.String path)

uid

public java.lang.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(java.lang.String value)

setFeaturesCol

public IsotonicRegression setFeaturesCol(java.lang.String value)

setPredictionCol

public IsotonicRegression setPredictionCol(java.lang.String value)

setIsotonic

public IsotonicRegression setIsotonic(boolean value)

setWeightCol

public IsotonicRegression setWeightCol(java.lang.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.

Specified by:

copy in interface Params

Specified by:

copy in class Estimator<IsotonicRegressionModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()

fit

public IsotonicRegressionModel fit(DataFrame 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 ::

Derives the output schema from the input schema.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

isotonic

public BooleanParam isotonic()

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

Returns:

(undocumented)

getIsotonic

public boolean getIsotonic()

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()

hasWeightCol

public boolean hasWeightCol()

Checks whether the input has weight column.

extractWeightedLabeledPoints

public RDD<scala.Tuple3<java.lang.Object,java.lang.Object,java.lang.Object>> extractWeightedLabeledPoints(DataFrame dataset)

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

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema,
                                    boolean fitting)