Class ProbabilisticClassifier<FeaturesType,E extends ProbabilisticClassifier<FeaturesType,E,M>,M extends ProbabilisticClassificationModel<FeaturesType,M>>     
Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Estimator<M>
org.apache.spark.ml.Predictor<FeaturesType,E,M>
  
org.apache.spark.ml.classification.Classifier<FeaturesType,E,M>
  
org.apache.spark.ml.classification.ProbabilisticClassifier<FeaturesType,E,M>  
- Type Parameters:
- FeaturesType- Type of input features. E.g.,- Vector
- E- Concrete Estimator type
- M- Concrete Model type
- All Implemented Interfaces:
- Serializable,- org.apache.spark.internal.Logging,- ClassifierParams,- ProbabilisticClassifierParams,- Params,- HasFeaturesCol,- HasLabelCol,- HasPredictionCol,- HasProbabilityCol,- HasRawPredictionCol,- HasThresholds,- PredictorParams,- Identifiable
- Direct Known Subclasses:
- DecisionTreeClassifier,- FMClassifier,- GBTClassifier,- LogisticRegression,- MultilayerPerceptronClassifier,- NaiveBayes,- RandomForestClassifier
public abstract class ProbabilisticClassifier<FeaturesType,E extends ProbabilisticClassifier<FeaturesType,E,M>,M extends ProbabilisticClassificationModel<FeaturesType,M>>     
extends Classifier<FeaturesType,E,M>
implements ProbabilisticClassifierParams  
Single-label binary or multiclass classifier which can output class conditional probabilities.
 
- 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 TypeMethodDescriptionParam for Column name for predicted class conditional probabilities.setProbabilityCol(String value) setThresholds(double[] value) Param for Thresholds in multi-class classification to adjust the probability of predicting each class.Methods inherited from class org.apache.spark.ml.classification.ClassifierrawPredictionCol, setRawPredictionColMethods inherited from class org.apache.spark.ml.Predictorcopy, featuresCol, fit, labelCol, predictionCol, setFeaturesCol, setLabelCol, setPredictionCol, transformSchemaMethods 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.param.shared.HasFeaturesColfeaturesCol, getFeaturesColMethods inherited from interface org.apache.spark.ml.param.shared.HasLabelColgetLabelCol, labelColMethods inherited from interface org.apache.spark.ml.param.shared.HasPredictionColgetPredictionCol, predictionColMethods inherited from interface org.apache.spark.ml.param.shared.HasProbabilityColgetProbabilityColMethods inherited from interface org.apache.spark.ml.param.shared.HasRawPredictionColgetRawPredictionCol, rawPredictionColMethods inherited from interface org.apache.spark.ml.param.shared.HasThresholdsgetThresholdsMethods inherited from interface org.apache.spark.ml.util.IdentifiabletoString, uidMethods inherited from interface org.apache.spark.internal.LogginginitializeForcefully, 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, withLogContextMethods inherited from interface org.apache.spark.ml.param.Paramsclear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwnMethods inherited from interface org.apache.spark.ml.classification.ProbabilisticClassifierParamsvalidateAndTransformSchema
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Constructor Details- 
ProbabilisticClassifierpublic ProbabilisticClassifier()
 
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Method Details- 
probabilityColDescription copied from interface:HasProbabilityColParam for Column name for predicted class conditional probabilities. Note: Not all models output well-calibrated probability estimates! These probabilities should be treated as confidences, not precise probabilities.- Specified by:
- probabilityColin interface- HasProbabilityCol
- Returns:
- (undocumented)
 
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setProbabilityCol
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setThresholds
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thresholdsDescription copied from interface:HasThresholdsParam for Thresholds in multi-class classification to adjust the probability of predicting each class. Array must have length equal to the number of classes, with values > 0 excepting that at most one value may be 0. The class with largest value p/t is predicted, where p is the original probability of that class and t is the class's threshold.- Specified by:
- thresholdsin interface- HasThresholds
- Returns:
- (undocumented)
 
 
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