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 SummaryNested classes/interfaces inherited from interface org.apache.spark.internal.Loggingorg.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter
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Constructor SummaryConstructors
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Method SummaryModifier 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.PipelineStageparamsMethods inherited from class java.lang.Objectequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitMethods inherited from interface org.apache.spark.ml.util.DefaultParamsWritablewriteMethods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesColgetFeaturesColMethods inherited from interface org.apache.spark.ml.param.shared.HasLabelColgetLabelColMethods inherited from interface org.apache.spark.ml.param.shared.HasPredictionColgetPredictionColMethods inherited from interface org.apache.spark.ml.param.shared.HasWeightColgetWeightColMethods inherited from interface org.apache.spark.ml.util.IdentifiabletoStringMethods inherited from interface org.apache.spark.ml.regression.IsotonicRegressionBaseextractWeightedLabeledPoints, getFeatureIndex, getIsotonic, hasWeightCol, validateAndTransformSchemaMethods inherited from interface org.apache.spark.internal.LogginginitializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContextMethods inherited from interface org.apache.spark.ml.util.MLWritablesaveMethods inherited from interface org.apache.spark.ml.param.Paramsclear, 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- 
IsotonicRegression
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IsotonicRegressionpublic IsotonicRegression()
 
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Method Details- 
load
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read
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isotonicDescription copied from interface:IsotonicRegressionBaseParam for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false). Default: true- Specified by:
- isotonicin interface- IsotonicRegressionBase
- Returns:
- (undocumented)
 
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featureIndexDescription copied from interface:IsotonicRegressionBaseParam for the index of the feature iffeaturesColis a vector column (default:0), no effect otherwise.- Specified by:
- featureIndexin interface- IsotonicRegressionBase
- Returns:
- (undocumented)
 
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weightColDescription 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 interface- HasWeightCol
- Returns:
- (undocumented)
 
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predictionColDescription copied from interface:HasPredictionColParam for prediction column name.- Specified by:
- predictionColin interface- HasPredictionCol
- Returns:
- (undocumented)
 
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labelColDescription copied from interface:HasLabelColParam for label column name.- Specified by:
- labelColin interface- HasLabelCol
- Returns:
- (undocumented)
 
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featuresColDescription copied from interface:HasFeaturesColParam for features column name.- Specified by:
- featuresColin interface- HasFeaturesCol
- Returns:
- (undocumented)
 
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uidDescription copied from interface:IdentifiableAn immutable unique ID for the object and its derivatives.- Specified by:
- uidin interface- Identifiable
- 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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copyDescription 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 interface- Params
- Specified by:
- copyin class- Estimator<IsotonicRegressionModel>
- Parameters:
- extra- (undocumented)
- Returns:
- (undocumented)
 
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fitDescription copied from class:EstimatorFits a model to the input data.- Specified by:
- fitin class- Estimator<IsotonicRegressionModel>
- Parameters:
- dataset- (undocumented)
- Returns:
- (undocumented)
 
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transformSchemaDescription 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 class- PipelineStage
- Parameters:
- schema- (undocumented)
- Returns:
- (undocumented)
 
 
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