Package org.apache.spark.ml.classification
package org.apache.spark.ml.classification

ClassDescriptionAbstraction for binary classification results for a given model.Abstraction for binary logistic regression results for a given model.Binary logistic regression results for a given model.Abstraction for binary logistic regression training results.Binary logistic regression training results.Abstraction for BinaryRandomForestClassification results for a given model.Binary RandomForestClassification for a given model.Abstraction for BinaryRandomForestClassification training results.Binary RandomForestClassification training results.ClassificationModel<FeaturesType,
M extends ClassificationModel<FeaturesType, M>> Model produced by aClassifier
.Abstraction for multiclass classification results for a given model.Classifier<FeaturesType,E extends Classifier<FeaturesType, E, M>, M extends ClassificationModel<FeaturesType, M>> Singlelabel binary or multiclass classification.(private[spark]) Params for classification.Decision tree model (http://en.wikipedia.org/wiki/Decision_tree_learning) for classification.Decision tree learning algorithm (http://en.wikipedia.org/wiki/Decision_tree_learning) for classification.Model produced byFMClassifier
Abstraction for FMClassifier results for a given model.FMClassifier results for a given model.Abstraction for FMClassifier training results.FMClassifier training results.Factorization Machines learning algorithm for classification.Params for FMClassifier.GradientBoosted Trees (GBTs) (http://en.wikipedia.org/wiki/Gradient_boosting) model for classification.GradientBoosted Trees (GBTs) (http://en.wikipedia.org/wiki/Gradient_boosting) learning algorithm for classification.Linear SVM Model trained byLinearSVC
Params for linear SVM Classifier.Abstraction for LinearSVC results for a given model.LinearSVC results for a given model.Abstraction for LinearSVC training results.LinearSVC training results.Logistic regression.Model produced byLogisticRegression
.Params for logistic regression.Abstraction for logistic regression results for a given model.Multiclass logistic regression results for a given model.Abstraction for multiclass logistic regression training results.Multiclass logistic regression training results.Classification model based on the Multilayer Perceptron.Abstraction for MultilayerPerceptronClassification results for a given model.MultilayerPerceptronClassification results for a given model.Abstraction for MultilayerPerceptronClassification training results.MultilayerPerceptronClassification training results.Classifier trainer based on the Multilayer Perceptron.Params for Multilayer Perceptron.Naive Bayes Classifiers.Model produced byNaiveBayes
Params for Naive Bayes Classifiers.Reduction of Multiclass Classification to Binary Classification.Model produced byOneVsRest
.Params forOneVsRest
.ProbabilisticClassificationModel<FeaturesType,M extends ProbabilisticClassificationModel<FeaturesType, M>> Model produced by aProbabilisticClassifier
.ProbabilisticClassifier<FeaturesType,E extends ProbabilisticClassifier<FeaturesType, E, M>, M extends ProbabilisticClassificationModel<FeaturesType, M>> Singlelabel binary or multiclass classifier which can output class conditional probabilities.(private[classification]) Params for probabilistic classification.Random Forest model for classification.Abstraction for multiclass RandomForestClassification results for a given model.Multiclass RandomForestClassification results for a given model.Abstraction for multiclass RandomForestClassification training results.Multiclass RandomForestClassification training results.Random Forest learning algorithm for classification.Abstraction for training results.