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
,scala.Serializable
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.SparkShellLoggingFilter
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptionCreates a copy of this instance with the same UID and some extra params.final IntParam
Param for the index of the feature iffeaturesCol
is a vector column (default:0
), no effect otherwise.Param for features column name.Fits a model to the input data.final BooleanParam
isotonic()
Param for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false).labelCol()
Param for label column name.static IsotonicRegression
Param 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
params
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable
write
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.util.Identifiable
toString
Methods inherited from interface org.apache.spark.ml.regression.IsotonicRegressionBase
extractWeightedLabeledPoints, getFeatureIndex, getIsotonic, hasWeightCol, validateAndTransformSchema
Methods inherited from interface org.apache.spark.internal.Logging
initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq
Methods inherited from interface org.apache.spark.ml.util.MLWritable
save
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
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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:IsotonicRegressionBase
Param for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false). Default: true- Specified by:
isotonic
in interfaceIsotonicRegressionBase
- Returns:
- (undocumented)
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featureIndex
Description copied from interface:IsotonicRegressionBase
Param for the index of the feature iffeaturesCol
is a vector column (default:0
), no effect otherwise.- Specified by:
featureIndex
in interfaceIsotonicRegressionBase
- Returns:
- (undocumented)
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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 interfaceHasWeightCol
- Returns:
- (undocumented)
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predictionCol
Description copied from interface:HasPredictionCol
Param for prediction column name.- Specified by:
predictionCol
in interfaceHasPredictionCol
- Returns:
- (undocumented)
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labelCol
Description copied from interface:HasLabelCol
Param for label column name.- Specified by:
labelCol
in interfaceHasLabelCol
- Returns:
- (undocumented)
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featuresCol
Description copied from interface:HasFeaturesCol
Param for features column name.- Specified by:
featuresCol
in interfaceHasFeaturesCol
- Returns:
- (undocumented)
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uid
Description copied from interface:Identifiable
An immutable unique ID for the object and its derivatives.- Specified by:
uid
in 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: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. SeedefaultCopy()
.- Specified by:
copy
in interfaceParams
- Specified by:
copy
in classEstimator<IsotonicRegressionModel>
- Parameters:
extra
- (undocumented)- Returns:
- (undocumented)
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fit
Description copied from class:Estimator
Fits a model to the input data.- Specified by:
fit
in classEstimator<IsotonicRegressionModel>
- Parameters:
dataset
- (undocumented)- Returns:
- (undocumented)
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transformSchema
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 byParam.validate()
.Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
- Specified by:
transformSchema
in classPipelineStage
- Parameters:
schema
- (undocumented)- Returns:
- (undocumented)
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