Package org.apache.spark.ml.classification

Interface Summary

Interface	Description
BinaryLogisticRegressionSummary	Abstraction for binary logistic regression results for a given model.
BinaryLogisticRegressionTrainingSummary	Abstraction for binary logistic regression training results.
ClassifierParams	(private[spark]) Params for classification.
ClassifierTypeTrait
FMClassifierParams	Params for FMClassifier.
LinearSVCParams	Params for linear SVM Classifier.
LogisticRegressionParams	Params for logistic regression.
LogisticRegressionSummary	Abstraction for logistic regression results for a given model.
LogisticRegressionTrainingSummary	Abstraction for multiclass logistic regression training results.
MultilayerPerceptronParams	Params for Multilayer Perceptron.
NaiveBayesParams	Params for Naive Bayes Classifiers.
OneVsRestParams	Params for OneVsRest.
ProbabilisticClassifierParams	(private[classification]) Params for probabilistic classification.

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>>	Model produced by a Classifier.
Classifier<FeaturesType,E extends Classifier<FeaturesType,E,M>,M extends ClassificationModel<FeaturesType,M>>	Single-label binary or multiclass classification.
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.
FMClassificationModel	Model produced by FMClassifier
FMClassifier	Factorization Machines learning algorithm 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	Linear SVM Classifier
LinearSVCModel	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
OneVsRest	Reduction of Multiclass Classification to Binary Classification.
OneVsRestModel	Model produced by OneVsRest.
ProbabilisticClassificationModel<FeaturesType,M extends ProbabilisticClassificationModel<FeaturesType,M>>	Model produced by a ProbabilisticClassifier.
ProbabilisticClassifier<FeaturesType,E extends ProbabilisticClassifier<FeaturesType,E,M>,M extends ProbabilisticClassificationModel<FeaturesType,M>>	Single-label binary or multiclass classifier which can output class conditional probabilities.
RandomForestClassificationModel	Random Forest model for classification.
RandomForestClassifier	Random Forest learning algorithm for classification.