org.apache.spark.ml.regression

Class IsotonicRegressionModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

org.apache.spark.ml.regression.IsotonicRegressionModel

All Implemented Interfaces:

java.io.Serializable, Params, Identifiable, MLWritable

public class IsotonicRegressionModel
extends Model<IsotonicRegressionModel>
implements MLWritable

Model fitted by IsotonicRegression. Predicts using a piecewise linear function.

For detailed rules see org.apache.spark.mllib.regression.IsotonicRegressionModel.predict().

param: oldModel A IsotonicRegressionModel model trained by IsotonicRegression.

See Also:

Serialized Form

Method Summary

Methods

Modifier and Type	Method and Description
Vector	boundaries() Boundaries in increasing order for which predictions are known.
static Params	clear(Param<?> param)
IsotonicRegressionModel	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()
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)
static boolean	hasParent()
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 IsotonicRegressionModel	load(String path)
static Param<?>[]	params()
static void	parent_$eq(Estimator<M> x$1)
static Estimator<M>	parent()
static Param<String>	predictionCol()
Vector	predictions() Predictions associated with the boundaries at the same index, monotone because of isotonic regression.
static MLReader<IsotonicRegressionModel>	read()
static void	save(String path)
static <T> Params	set(Param<T> param, T value)
IsotonicRegressionModel	setFeatureIndex(int value)
IsotonicRegressionModel	setFeaturesCol(String value)
static M	setParent(Estimator<M> parent)
IsotonicRegressionModel	setPredictionCol(String value)
static String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
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 void	validateParams()
static Param<String>	weightCol()
MLWriter	write() Returns an MLWriter instance for this ML instance.

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

hasParent, parent, setParent

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

transform, transform, transform

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, validateParams

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

toString

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

save

Method Detail

read

public static MLReader<IsotonicRegressionModel> read()

load

public static IsotonicRegressionModel load(String path)

toString

public static String toString()

params

public static Param<?>[] params()

validateParams

public static void validateParams()

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()

parent

public static Estimator<M> parent()

parent_$eq

public static void parent_$eq(Estimator<M> x$1)

setParent

public static M setParent(Estimator<M> parent)

hasParent

public static boolean hasParent()

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

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)

setFeaturesCol

public IsotonicRegressionModel setFeaturesCol(String value)

setPredictionCol

public IsotonicRegressionModel setPredictionCol(String value)

setFeatureIndex

public IsotonicRegressionModel setFeatureIndex(int value)

boundaries

public Vector boundaries()

Boundaries in increasing order for which predictions are known.

predictions

public Vector predictions()

Predictions associated with the boundaries at the same index, monotone because of isotonic regression.

Returns:

(undocumented)

copy

public IsotonicRegressionModel 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 Model<IsotonicRegressionModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

transform

public Dataset<Row> transform(Dataset<?> dataset)

Description copied from class: Transformer

Transforms the input dataset.

Specified by:

transform in class Transformer

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.

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)

write

public MLWriter write()

Description copied from interface: MLWritable

Returns an MLWriter instance for this ML instance.

Specified by:

write in interface MLWritable

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<Object,Object,Object>> extractWeightedLabeledPoints(Dataset<?> dataset)

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

Parameters:

dataset - (undocumented)

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