classification

Type Members

1. class BinaryLogisticRegressionSummary extends LogisticRegressionSummary

   :: Experimental :: Binary Logistic regression results for a given model.

2. class BinaryLogisticRegressionTrainingSummary extends BinaryLogisticRegressionSummary with LogisticRegressionTrainingSummary

   :: Experimental :: Logistic regression training results.

3. abstract class ClassificationModel[FeaturesType, M <: ClassificationModel[FeaturesType, M]] extends PredictionModel[FeaturesType, M] with ClassifierParams

   :: DeveloperApi ::

4. abstract class Classifier[FeaturesType, E <: Classifier[FeaturesType, E, M], M <: ClassificationModel[FeaturesType, M]] extends Predictor[FeaturesType, E, M] with ClassifierParams

   :: DeveloperApi ::

5. final class DecisionTreeClassificationModel extends ProbabilisticClassificationModel[Vector, DecisionTreeClassificationModel] with DecisionTreeModel with Serializable

   :: Experimental :: Decision tree model for classification.

6. final class DecisionTreeClassifier extends ProbabilisticClassifier[Vector, DecisionTreeClassifier, DecisionTreeClassificationModel] with DecisionTreeParams with TreeClassifierParams

   :: Experimental :: Decision tree learning algorithm for classification.

7. final class GBTClassificationModel extends PredictionModel[Vector, GBTClassificationModel] with TreeEnsembleModel with Serializable

   :: Experimental :: Gradient-Boosted Trees (GBTs) model for classification.

8. final class GBTClassifier extends Predictor[Vector, GBTClassifier, GBTClassificationModel] with GBTParams with TreeClassifierParams with Logging

   :: Experimental :: Gradient-Boosted Trees (GBTs) learning algorithm for classification.

9. class LogisticRegression extends ProbabilisticClassifier[Vector, LogisticRegression, LogisticRegressionModel] with LogisticRegressionParams with DefaultParamsWritable with Logging

   :: Experimental :: Logistic regression.

10. class LogisticRegressionModel extends ProbabilisticClassificationModel[Vector, LogisticRegressionModel] with LogisticRegressionParams with MLWritable

    :: Experimental :: Model produced by LogisticRegression.

11. sealed trait LogisticRegressionSummary extends Serializable

    Abstraction for Logistic Regression Results for a given model.

12. sealed trait LogisticRegressionTrainingSummary extends LogisticRegressionSummary

    Abstraction for multinomial Logistic Regression Training results.

13. class MultilayerPerceptronClassificationModel extends PredictionModel[Vector, MultilayerPerceptronClassificationModel] with Serializable

    :: Experimental :: Classification model based on the Multilayer Perceptron.

14. class MultilayerPerceptronClassifier extends Predictor[Vector, MultilayerPerceptronClassifier, MultilayerPerceptronClassificationModel] with MultilayerPerceptronParams

    :: Experimental :: Classifier trainer based on the Multilayer Perceptron.

15. class NaiveBayes extends ProbabilisticClassifier[Vector, NaiveBayes, NaiveBayesModel] with NaiveBayesParams with DefaultParamsWritable

    :: Experimental :: Naive Bayes Classifiers.

16. class NaiveBayesModel extends ProbabilisticClassificationModel[Vector, NaiveBayesModel] with NaiveBayesParams with MLWritable

    :: Experimental :: Model produced by NaiveBayes

17. final class OneVsRest extends Estimator[OneVsRestModel] with OneVsRestParams

    :: Experimental ::

18. final class OneVsRestModel extends Model[OneVsRestModel] with OneVsRestParams

    :: Experimental :: Model produced by OneVsRest.

19. abstract class ProbabilisticClassificationModel[FeaturesType, M <: ProbabilisticClassificationModel[FeaturesType, M]] extends ClassificationModel[FeaturesType, M] with ProbabilisticClassifierParams

    :: DeveloperApi ::

20. abstract class ProbabilisticClassifier[FeaturesType, E <: ProbabilisticClassifier[FeaturesType, E, M], M <: ProbabilisticClassificationModel[FeaturesType, M]] extends Classifier[FeaturesType, E, M] with ProbabilisticClassifierParams

    :: DeveloperApi ::

21. final class RandomForestClassificationModel extends ProbabilisticClassificationModel[Vector, RandomForestClassificationModel] with TreeEnsembleModel with Serializable

    :: Experimental :: Random Forest model for classification.

22. final class RandomForestClassifier extends ProbabilisticClassifier[Vector, RandomForestClassifier, RandomForestClassificationModel] with RandomForestParams with TreeClassifierParams

    :: Experimental :: Random Forest learning algorithm for classification.