Package org.apache.spark.ml.classification

Class Summary

ClassificationModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>>	:: DeveloperApi ::
Classifier<FeaturesType,E extends Classifier<FeaturesType,E,M>,M extends ClassificationModel<FeaturesType,M>>	:: DeveloperApi ::
DecisionTreeClassificationModel	:: Experimental :: Decision tree model for classification.
DecisionTreeClassifier	:: Experimental :: Decision tree learning algorithm for classification.
GBTClassificationModel	:: Experimental :: Gradient-Boosted Trees (GBTs) model for classification.
GBTClassifier	:: Experimental :: Gradient-Boosted Trees (GBTs) learning algorithm for classification.
LogisticAggregator	LogisticAggregator computes the gradient and loss for binary logistic loss function, as used in binary classification for samples in sparse or dense vector in a online fashion.
LogisticCostFun	LogisticCostFun implements Breeze's DiffFunction[T] for a multinomial logistic loss function, as used in multi-class classification (it is also used in binary logistic regression).
LogisticRegression	:: Experimental :: Logistic regression.
LogisticRegressionModel	:: Experimental :: Model produced by LogisticRegression.
OneVsRest	:: Experimental ::
OneVsRestModel	:: Experimental :: Model produced by OneVsRest.
RandomForestClassificationModel	:: Experimental :: Random Forest model for classification.
RandomForestClassifier	:: Experimental :: Random Forest learning algorithm for classification.