Class OneVsRestModel
- All Implemented Interfaces:
- Serializable,- org.apache.spark.internal.Logging,- ClassifierParams,- ClassifierTypeTrait,- OneVsRestParams,- Params,- HasFeaturesCol,- HasLabelCol,- HasPredictionCol,- HasRawPredictionCol,- HasWeightCol,- PredictorParams,- Identifiable,- MLWritable
OneVsRest.
 This stores the models resulting from training k binary classifiers: one for each class.
 Each example is scored against all k models, and the model with the highest score
 is picked to label the example.
 param: labelMetadata Metadata of label column if it exists, or Nominal attribute representing the number of classes in training dataset otherwise. param: models The binary classification models for the reduction. The i-th model is produced by testing the i-th class (taking label 1) vs the rest (taking label 0).
- 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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Method SummaryModifier 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.labelCol()Param for label column name.static OneVsRestModelmodels()intintParam for prediction column name.Param for raw prediction (a.k.a.static MLReader<OneVsRestModel>read()setFeaturesCol(String value) setPredictionCol(String value) setRawPredictionCol(String value) toString()Transforms the input dataset.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 anMLWriterinstance for this ML instance.Methods inherited from class org.apache.spark.ml.Transformertransform, transform, transformMethods inherited from class org.apache.spark.ml.PipelineStageparamsMethods inherited from class java.lang.Objectequals, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface org.apache.spark.ml.classification.ClassifierParamsvalidateAndTransformSchemaMethods 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.HasRawPredictionColgetRawPredictionColMethods inherited from interface org.apache.spark.ml.param.shared.HasWeightColgetWeightColMethods 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.classification.OneVsRestParamsgetClassifierMethods 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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Method Details- 
read
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load
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classifierpublic Param<Classifier<?,? extends Classifier<Object, classifier()Classifier, ClassificationModel>, ? extends ClassificationModel<Object, ClassificationModel>>> Description copied from interface:OneVsRestParamsparam 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:
- classifierin interface- OneVsRestParams
- 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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rawPredictionColDescription copied from interface:HasRawPredictionColParam for raw prediction (a.k.a. confidence) column name.- Specified by:
- rawPredictionColin interface- HasRawPredictionCol
- 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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featuresColDescription copied from interface:HasFeaturesColParam for features column name.- Specified by:
- featuresColin interface- HasFeaturesCol
- 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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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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models
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numClassespublic int numClasses()
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numFeaturespublic int numFeatures()
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setFeaturesCol
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setPredictionCol
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setRawPredictionCol
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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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transformDescription copied from class:TransformerTransforms the input dataset.- Specified by:
- transformin class- Transformer
- Parameters:
- dataset- (undocumented)
- Returns:
- (undocumented)
 
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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- Model<OneVsRestModel>
- Parameters:
- extra- (undocumented)
- Returns:
- (undocumented)
 
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writeDescription copied from interface:MLWritableReturns anMLWriterinstance for this ML instance.- Specified by:
- writein interface- MLWritable
- Returns:
- (undocumented)
 
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toString- Specified by:
- toStringin interface- Identifiable
- Overrides:
- toStringin class- Object
 
 
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