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, org.apache.spark.internal.Logging, Params, HasFeaturesCol, HasLabelCol, HasPredictionCol, HasWeightCol, IsotonicRegressionBase, DefaultParamsWritable, Identifiable, MLWritable

public class IsotonicRegression
extends Estimator<IsotonicRegressionModel>
implements IsotonicRegressionBase, 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
IsotonicRegression	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
IntParam	featureIndex() Param for the index of the feature if featuresCol is a vector column (default: 0), no effect otherwise.
Param<String>	featuresCol() Param for features column name.
IsotonicRegressionModel	fit(Dataset<?> dataset) Fits a model to the input data.
BooleanParam	isotonic() Param for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false).
Param<String>	labelCol() Param for label column name.
static IsotonicRegression	load(String path)
Param<String>	predictionCol() Param for prediction column name.
static MLReader<T>	read()
IsotonicRegression	setFeatureIndex(int value)
IsotonicRegression	setFeaturesCol(String value)
IsotonicRegression	setIsotonic(boolean value)
IsotonicRegression	setLabelCol(String value)
IsotonicRegression	setPredictionCol(String value)
IsotonicRegression	setWeightCol(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.
Param<String>	weightCol() Param for weight column name.

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.regression.IsotonicRegressionBase

extractWeightedLabeledPoints, getFeatureIndex, getIsotonic, hasWeightCol, validateAndTransformSchema

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

getFeaturesCol

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

getLabelCol

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

getPredictionCol

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

getWeightCol

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

$init$, 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

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)

read

public static MLReader<T> read()

isotonic

public final BooleanParam isotonic()

Description copied from interface: IsotonicRegressionBase

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

Specified by:

isotonic in interface IsotonicRegressionBase

Returns:

(undocumented)

featureIndex

public final IntParam featureIndex()

Description copied from interface: IsotonicRegressionBase

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

Specified by:

featureIndex in interface IsotonicRegressionBase

Returns:

(undocumented)

weightCol

public final Param<String> weightCol()

Description copied from interface: HasWeightCol

Param for weight column name. If this is not set or empty, we treat all instance weights as 1.0.

Specified by:

weightCol in interface HasWeightCol

Returns:

(undocumented)

predictionCol

public final Param<String> predictionCol()

Description copied from interface: HasPredictionCol

Param for prediction column name.

Specified by:

predictionCol in interface HasPredictionCol

Returns:

(undocumented)

labelCol

public final Param<String> labelCol()

Description copied from interface: HasLabelCol

Param for label column name.

Specified by:

labelCol in interface HasLabelCol

Returns:

(undocumented)

featuresCol

public final Param<String> featuresCol()

Description copied from interface: HasFeaturesCol

Param for features column name.

Specified by:

featuresCol in interface HasFeaturesCol

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)

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

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)