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 typeM
- Concrete Model type
- All Implemented Interfaces:
Serializable
,org.apache.spark.internal.Logging
,ClassifierParams
,ProbabilisticClassifierParams
,Params
,HasFeaturesCol
,HasLabelCol
,HasPredictionCol
,HasProbabilityCol
,HasRawPredictionCol
,HasThresholds
,PredictorParams
,Identifiable
,scala.Serializable
- 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:
-
Nested Class Summary
Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging
org.apache.spark.internal.Logging.SparkShellLoggingFilter
-
Constructor Summary
-
Method Summary
Modifier 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.Classifier
rawPredictionCol, setRawPredictionCol
Methods inherited from class org.apache.spark.ml.Predictor
copy, featuresCol, fit, labelCol, predictionCol, setFeaturesCol, setLabelCol, setPredictionCol, transformSchema
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.param.shared.HasFeaturesCol
featuresCol, getFeaturesCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasLabelCol
getLabelCol, labelCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol
getPredictionCol, predictionCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasProbabilityCol
getProbabilityCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasRawPredictionCol
getRawPredictionCol, rawPredictionCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasThresholds
getThresholds
Methods inherited from interface org.apache.spark.ml.util.Identifiable
toString, uid
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.param.Params
clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
Methods inherited from interface org.apache.spark.ml.classification.ProbabilisticClassifierParams
validateAndTransformSchema
-
Constructor Details
-
ProbabilisticClassifier
public ProbabilisticClassifier()
-
-
Method Details
-
probabilityCol
Description copied from interface:HasProbabilityCol
Param 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:
probabilityCol
in interfaceHasProbabilityCol
- Returns:
- (undocumented)
-
setProbabilityCol
-
setThresholds
-
thresholds
Description copied from interface:HasThresholds
Param 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:
thresholds
in interfaceHasThresholds
- Returns:
- (undocumented)
-