Class OneVsRest
- All Implemented Interfaces:
Serializable
,org.apache.spark.internal.Logging
,ClassifierParams
,ClassifierTypeTrait
,OneVsRestParams
,Params
,HasFeaturesCol
,HasLabelCol
,HasParallelism
,HasPredictionCol
,HasRawPredictionCol
,HasWeightCol
,PredictorParams
,Identifiable
,MLWritable
public final class OneVsRest
extends Estimator<OneVsRestModel>
implements OneVsRestParams, HasParallelism, MLWritable
Reduction of Multiclass Classification to Binary Classification.
Performs reduction using one against all strategy.
For a multiclass classification with k classes, train k models (one per class).
Each example is scored against all k models and the model with highest score
is picked to label the example.
- 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
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptionParam<Classifier<?,
? extends Classifier<Object, Classifier, ClassificationModel>, ? extends ClassificationModel<Object, ClassificationModel>>> param for the base binary classifier that we reduce multiclass classification into.Creates a copy of this instance with the same UID and some extra params.Param for features column name.Fits a model to the input data.labelCol()
Param for label column name.static OneVsRest
The number of threads to use when running parallel algorithms.Param for prediction column name.Param for raw prediction (a.k.a.read()
setClassifier
(Classifier<?, ?, ?> value) setFeaturesCol
(String value) setLabelCol
(String value) setParallelism
(int value) The implementation of parallel one vs.setPredictionCol
(String value) setRawPredictionCol
(String value) setWeightCol
(String value) Sets the value of paramweightCol()
.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.write()
Returns anMLWriter
instance for this ML instance.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.classification.ClassifierParams
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.HasParallelism
getExecutionContext, getParallelism
Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol
getPredictionCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasRawPredictionCol
getRawPredictionCol
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.internal.Logging
initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext
Methods inherited from interface org.apache.spark.ml.util.MLWritable
save
Methods inherited from interface org.apache.spark.ml.classification.OneVsRestParams
getClassifier
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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OneVsRest
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OneVsRest
public OneVsRest()
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Method Details
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read
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load
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parallelism
Description copied from interface:HasParallelism
The number of threads to use when running parallel algorithms. Default is 1 for serial execution- Specified by:
parallelism
in interfaceHasParallelism
- Returns:
- (undocumented)
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classifier
public Param<Classifier<?,? extends Classifier<Object, classifier()Classifier, ClassificationModel>, ? extends ClassificationModel<Object, ClassificationModel>>> Description copied from interface:OneVsRestParams
param for the base binary classifier that we reduce multiclass classification into. The base classifier input and output columns are ignored in favor of the ones specified inOneVsRest
.- Specified by:
classifier
in interfaceOneVsRestParams
- 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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rawPredictionCol
Description copied from interface:HasRawPredictionCol
Param for raw prediction (a.k.a. confidence) column name.- Specified by:
rawPredictionCol
in interfaceHasRawPredictionCol
- 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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featuresCol
Description copied from interface:HasFeaturesCol
Param for features column name.- Specified by:
featuresCol
in interfaceHasFeaturesCol
- 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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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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setClassifier
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setLabelCol
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setFeaturesCol
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setPredictionCol
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setRawPredictionCol
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setParallelism
The implementation of parallel one vs. rest runs the classification for each class in a separate threads.- Parameters:
value
- (undocumented)- Returns:
- (undocumented)
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setWeightCol
Sets the value of paramweightCol()
.This is ignored if weight is not supported by
classifier()
. If this is not set or empty, we treat all instance weights as 1.0. Default is not set, so all instances have weight one.- Parameters:
value
- (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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fit
Description copied from class:Estimator
Fits a model to the input data.- Specified by:
fit
in classEstimator<OneVsRestModel>
- Parameters:
dataset
- (undocumented)- Returns:
- (undocumented)
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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<OneVsRestModel>
- Parameters:
extra
- (undocumented)- Returns:
- (undocumented)
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write
Description copied from interface:MLWritable
Returns anMLWriter
instance for this ML instance.- Specified by:
write
in interfaceMLWritable
- Returns:
- (undocumented)
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