Package 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:
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:
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Nested Class Summary
Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging
org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionCreates a copy of this instance with the same UID and some extra params.final IntParamParam for the index of the feature iffeaturesColis a vector column (default:0), no effect otherwise.Param for features column name.Fits a model to the input data.final BooleanParamisotonic()Param for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false).labelCol()Param for label column name.static IsotonicRegressionParam for prediction column name.static MLReader<T>read()setFeatureIndex(int value) setFeaturesCol(String value) setIsotonic(boolean value) setLabelCol(String value) setPredictionCol(String value) setWeightCol(String value) transformSchema(StructType schema) Check transform validity and derive the output schema from the input schema.uid()An immutable unique ID for the object and its derivatives.Param for weight column name.Methods inherited from class org.apache.spark.ml.PipelineStage
paramsMethods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitMethods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable
writeMethods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesCol
getFeaturesColMethods inherited from interface org.apache.spark.ml.param.shared.HasLabelCol
getLabelColMethods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol
getPredictionColMethods inherited from interface org.apache.spark.ml.param.shared.HasWeightCol
getWeightColMethods inherited from interface org.apache.spark.ml.util.Identifiable
toStringMethods inherited from interface org.apache.spark.ml.regression.IsotonicRegressionBase
extractWeightedLabeledPoints, getFeatureIndex, getIsotonic, hasWeightCol, validateAndTransformSchemaMethods inherited from interface org.apache.spark.internal.Logging
initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContextMethods inherited from interface org.apache.spark.ml.util.MLWritable
saveMethods inherited from interface org.apache.spark.ml.param.Params
clear, copyValues, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
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Constructor Details
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IsotonicRegression
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IsotonicRegression
public IsotonicRegression()
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Method Details
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load
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read
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isotonic
Description copied from interface:IsotonicRegressionBaseParam for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false). Default: true- Specified by:
isotonicin interfaceIsotonicRegressionBase- Returns:
- (undocumented)
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featureIndex
Description copied from interface:IsotonicRegressionBaseParam for the index of the feature iffeaturesColis a vector column (default:0), no effect otherwise.- Specified by:
featureIndexin interfaceIsotonicRegressionBase- Returns:
- (undocumented)
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weightCol
Description copied from interface:HasWeightColParam for weight column name. If this is not set or empty, we treat all instance weights as 1.0.- Specified by:
weightColin interfaceHasWeightCol- Returns:
- (undocumented)
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predictionCol
Description copied from interface:HasPredictionColParam for prediction column name.- Specified by:
predictionColin interfaceHasPredictionCol- Returns:
- (undocumented)
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labelCol
Description copied from interface:HasLabelColParam for label column name.- Specified by:
labelColin interfaceHasLabelCol- Returns:
- (undocumented)
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featuresCol
Description copied from interface:HasFeaturesColParam for features column name.- Specified by:
featuresColin interfaceHasFeaturesCol- Returns:
- (undocumented)
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uid
Description copied from interface:IdentifiableAn immutable unique ID for the object and its derivatives.- Specified by:
uidin interfaceIdentifiable- Returns:
- (undocumented)
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setLabelCol
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setFeaturesCol
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setPredictionCol
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setIsotonic
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setWeightCol
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setFeatureIndex
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copy
Description copied from interface:ParamsCreates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. SeedefaultCopy().- Specified by:
copyin interfaceParams- Specified by:
copyin classEstimator<IsotonicRegressionModel>- Parameters:
extra- (undocumented)- Returns:
- (undocumented)
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fit
Description copied from class:EstimatorFits a model to the input data.- Specified by:
fitin classEstimator<IsotonicRegressionModel>- Parameters:
dataset- (undocumented)- Returns:
- (undocumented)
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transformSchema
Description copied from class:PipelineStageCheck transform validity and derive the output schema from the input schema.We check validity for interactions between parameters during
transformSchemaand raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled byParam.validate().Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
- Specified by:
transformSchemain classPipelineStage- Parameters:
schema- (undocumented)- Returns:
- (undocumented)
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