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  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>> 
Singlelabel 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 
GradientBoosted Trees (GBTs) (http://en.wikipedia.org/wiki/Gradient_boosting)
model for classification.

GBTClassifier 
GradientBoosted Trees (GBTs) (http://en.wikipedia.org/wiki/Gradient_boosting)
learning algorithm for classification.

LinearSVC  
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>> 
Singlelabel binary or multiclass classifier which can output class conditional probabilities.

RandomForestClassificationModel 
Random Forest model for classification.

RandomForestClassifier 
Random Forest learning algorithm for
classification.
