Package org.apache.spark.ml.classification

package org.apache.spark.ml.classification

Related Packages

Package	Description
org.apache.spark.ml	DataFrame-based machine learning APIs to let users quickly assemble and configure practical machine learning pipelines.

Class	Description
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.
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
FMClassificationModel.Data$
FMClassificationSummary	Abstraction for FMClassifier results for a given model.
FMClassificationTrainingSummary	Abstraction for 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
LinearSVCModel.Data$
LinearSVCSummary	Abstraction for LinearSVC results for a given model.
LinearSVCTrainingSummary	Abstraction for LinearSVC training results.
LogisticRegression	Logistic regression.
LogisticRegressionModel	Model produced by LogisticRegression.
LogisticRegressionModel.Data$
LogisticRegressionSummary	Abstraction for logistic regression results for a given model.
LogisticRegressionTrainingSummary	Abstraction for multiclass logistic regression training results.
MultilayerPerceptronClassificationModel	Classification model based on the Multilayer Perceptron.
MultilayerPerceptronClassificationModel.Data$
MultilayerPerceptronClassificationSummary	Abstraction for MultilayerPerceptronClassification results for a given model.
MultilayerPerceptronClassificationTrainingSummary	Abstraction for MultilayerPerceptronClassification training results.
MultilayerPerceptronClassifier	Classifier trainer based on the Multilayer Perceptron.
NaiveBayes	Naive Bayes Classifiers.
NaiveBayesModel	Model produced by NaiveBayes
NaiveBayesModel.Data$
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.
RandomForestClassificationSummary	Abstraction for multiclass RandomForestClassification results for a given model.
RandomForestClassificationTrainingSummary	Abstraction for multiclass RandomForestClassification training results.
RandomForestClassifier	Random Forest learning algorithm for classification.