Package org.apache.spark.ml.classification

Interface Summary

Interface	Description
BinaryClassificationSummary	Abstraction for binary classification results for a given model.
BinaryLogisticRegressionSummary	Abstraction for binary logistic regression results for a given model.
BinaryLogisticRegressionTrainingSummary	Abstraction for binary logistic regression training results.
BinaryRandomForestClassificationSummary	Abstraction for BinaryRandomForestClassification results for a given model.
BinaryRandomForestClassificationTrainingSummary	Abstraction for BinaryRandomForestClassification training results.
ClassificationSummary	Abstraction for multiclass classification results for a given model.
ClassifierParams	(private[spark]) Params for classification.
ClassifierTypeTrait
FMClassificationSummary	Abstraction for FMClassifier results for a given model.
FMClassificationTrainingSummary	Abstraction for FMClassifier training results.
FMClassifierParams	Params for FMClassifier.
LinearSVCParams	Params for linear SVM Classifier.
LinearSVCSummary	Abstraction for LinearSVC results for a given model.
LinearSVCTrainingSummary	Abstraction for LinearSVC training results.
LogisticRegressionParams	Params for logistic regression.
LogisticRegressionSummary	Abstraction for logistic regression results for a given model.
LogisticRegressionTrainingSummary	Abstraction for multiclass logistic regression training results.
MultilayerPerceptronClassificationSummary	Abstraction for MultilayerPerceptronClassification results for a given model.
MultilayerPerceptronClassificationTrainingSummary	Abstraction for MultilayerPerceptronClassification training results.
MultilayerPerceptronParams	Params for Multilayer Perceptron.
NaiveBayesParams	Params for Naive Bayes Classifiers.
OneVsRestParams	Params for OneVsRest.
ProbabilisticClassifierParams	(private[classification]) Params for probabilistic classification.
RandomForestClassificationSummary	Abstraction for multiclass RandomForestClassification results for a given model.
RandomForestClassificationTrainingSummary	Abstraction for multiclass RandomForestClassification training results.
TrainingSummary	Abstraction for training results.

Class Summary

Class	Description
BinaryLogisticRegressionSummaryImpl	Binary logistic regression results for a given model.
BinaryLogisticRegressionTrainingSummaryImpl	Binary logistic regression training results.
BinaryRandomForestClassificationSummaryImpl	Binary RandomForestClassification for a given model.
BinaryRandomForestClassificationTrainingSummaryImpl	Binary RandomForestClassification 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
FMClassificationSummaryImpl	FMClassifier results for a given model.
FMClassificationTrainingSummaryImpl	FMClassifier training results.
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
LinearSVCSummaryImpl	LinearSVC results for a given model.
LinearSVCTrainingSummaryImpl	LinearSVC training results.
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.
MultilayerPerceptronClassificationSummaryImpl	MultilayerPerceptronClassification results for a given model.
MultilayerPerceptronClassificationTrainingSummaryImpl	MultilayerPerceptronClassification training results.
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.
RandomForestClassificationSummaryImpl	Multiclass RandomForestClassification results for a given model.
RandomForestClassificationTrainingSummaryImpl	Multiclass RandomForestClassification training results.
RandomForestClassifier	Random Forest learning algorithm for classification.