Package org.apache.spark.ml.classification

Interface Summary

Interface	Description
BinaryLogisticRegressionSummary	:: Experimental :: Abstraction for binary logistic regression results for a given model.
BinaryLogisticRegressionTrainingSummary	:: Experimental :: Abstraction for binary logistic regression training results.
LogisticRegressionSummary	:: Experimental :: Abstraction for logistic regression results for a given model.
LogisticRegressionTrainingSummary	:: Experimental :: Abstraction for multiclass logistic regression training results.

Class Summary

Class	Description
BinaryLogisticRegressionSummaryImpl	Binary logistic regression results for a given model.
BinaryLogisticRegressionTrainingSummaryImpl	Binary logistic regression training results.
ClassificationModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>>	:: DeveloperApi ::
Classifier<FeaturesType,E extends Classifier<FeaturesType,E,M>,M extends ClassificationModel<FeaturesType,M>>	:: DeveloperApi ::
DecisionTreeClassificationModel	Decision tree model (http://en.wikipedia.org/wiki/Decision_tree_learning) for classification.
DecisionTreeClassifier	Decision tree learning algorithm (http://en.wikipedia.org/wiki/Decision_tree_learning) for classification.
GBTClassificationModel	Gradient-Boosted Trees (GBTs) (http://en.wikipedia.org/wiki/Gradient_boosting) model for classification.
GBTClassifier	Gradient-Boosted Trees (GBTs) (http://en.wikipedia.org/wiki/Gradient_boosting) learning algorithm for classification.
LinearSVC	:: Experimental ::
LinearSVCModel	:: Experimental :: Linear SVM Model trained by LinearSVC
LogisticRegression	Logistic regression.
LogisticRegressionModel	Model produced by LogisticRegression.
LogisticRegressionSummaryImpl	Multiclass logistic regression results for a given model.
LogisticRegressionTrainingSummaryImpl	Multiclass logistic regression training results.
MultilayerPerceptronClassificationModel	Classification model based on the Multilayer Perceptron.
MultilayerPerceptronClassifier	Classifier trainer based on the Multilayer Perceptron.
NaiveBayes	Naive Bayes Classifiers.
NaiveBayesModel	Model produced by NaiveBayes param: pi log of class priors, whose dimension is C (number of classes) param: theta log of class conditional probabilities, whose dimension is C (number of classes) by D (number of features)
OneVsRest	Reduction of Multiclass Classification to Binary Classification.
OneVsRestModel	Model produced by OneVsRest.
ProbabilisticClassificationModel<FeaturesType,M extends ProbabilisticClassificationModel<FeaturesType,M>>	:: DeveloperApi ::
ProbabilisticClassifier<FeaturesType,E extends ProbabilisticClassifier<FeaturesType,E,M>,M extends ProbabilisticClassificationModel<FeaturesType,M>>	:: DeveloperApi ::
RandomForestClassificationModel	Random Forest model for classification.
RandomForestClassifier	Random Forest learning algorithm for classification.