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 | |
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>> |
:: DeveloperApi ::
|
Classifier<FeaturesType,E extends Classifier<FeaturesType,E,M>,M extends ClassificationModel<FeaturesType,M>> |
:: DeveloperApi ::
|
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.
|
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 | |
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>> |
:: DeveloperApi ::
|
ProbabilisticClassifier<FeaturesType,E extends ProbabilisticClassifier<FeaturesType,E,M>,M extends ProbabilisticClassificationModel<FeaturesType,M>> |
:: DeveloperApi ::
|
RandomForestClassificationModel |
Random Forest model for classification.
|
RandomForestClassifier |
Random Forest learning algorithm for
classification.
|