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

public class IsotonicRegressionModel
extends Model<IsotonicRegressionModel>
implements IsotonicRegressionBase, 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

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.SparkShellLoggingFilter

Method Summary

Modifier and Type	Method and Description
Vector	boundaries() Boundaries in increasing order for which predictions are known.
IsotonicRegressionModel	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.
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 IsotonicRegressionModel	load(String path)
int	numFeatures()
double	predict(double value)
Param<String>	predictionCol() Param for prediction column name.
Vector	predictions() Predictions associated with the boundaries at the same index, monotone because of isotonic regression.
static MLReader<IsotonicRegressionModel>	read()
IsotonicRegressionModel	setFeatureIndex(int value)
IsotonicRegressionModel	setFeaturesCol(String value)
IsotonicRegressionModel	setPredictionCol(String value)
String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
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.
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 org.apache.spark.ml.PipelineStage

params

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, 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, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

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.MLWritable

save

Method Detail

read

public static MLReader<IsotonicRegressionModel> read()

load

public static IsotonicRegressionModel load(String path)

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)

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)

predict

public double predict(double value)

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)

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)

numFeatures

public int numFeatures()

toString

public String toString()

Specified by:

toString in interface Identifiable

Overrides:

toString in class Object