regression

Type Members

1. class AFTSurvivalRegression extends Estimator[AFTSurvivalRegressionModel] with AFTSurvivalRegressionParams with DefaultParamsWritable with Logging

   :: Experimental :: Fit a parametric survival regression model named accelerated failure time (AFT) model (https://en.wikipedia.org/wiki/Accelerated_failure_time_model) based on the Weibull distribution of the survival time.

2. class AFTSurvivalRegressionModel extends Model[AFTSurvivalRegressionModel] with AFTSurvivalRegressionParams with MLWritable

   :: Experimental :: Model produced by AFTSurvivalRegression.

3. final class DecisionTreeRegressionModel extends PredictionModel[Vector, DecisionTreeRegressionModel] with DecisionTreeModel with Serializable

   :: Experimental :: Decision tree model for regression.

4. final class DecisionTreeRegressor extends Predictor[Vector, DecisionTreeRegressor, DecisionTreeRegressionModel] with DecisionTreeParams with TreeRegressorParams

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

5. final class GBTRegressionModel extends PredictionModel[Vector, GBTRegressionModel] with TreeEnsembleModel with Serializable

   :: Experimental ::

6. final class GBTRegressor extends Predictor[Vector, GBTRegressor, GBTRegressionModel] with GBTParams with TreeRegressorParams with Logging

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

7. class IsotonicRegression extends Estimator[IsotonicRegressionModel] with IsotonicRegressionBase with DefaultParamsWritable

   :: Experimental :: Isotonic regression.

8. class IsotonicRegressionModel extends Model[IsotonicRegressionModel] with IsotonicRegressionBase with MLWritable

   :: Experimental :: Model fitted by IsotonicRegression.

9. class LinearRegression extends Regressor[Vector, LinearRegression, LinearRegressionModel] with LinearRegressionParams with DefaultParamsWritable with Logging

   :: Experimental :: Linear regression.

10. class LinearRegressionModel extends RegressionModel[Vector, LinearRegressionModel] with LinearRegressionParams with MLWritable

    :: Experimental :: Model produced by LinearRegression.

11. class LinearRegressionSummary extends Serializable

    :: Experimental :: Linear regression results evaluated on a dataset.

12. class LinearRegressionTrainingSummary extends LinearRegressionSummary

    :: Experimental :: Linear regression training results.

13. final class RandomForestRegressionModel extends PredictionModel[Vector, RandomForestRegressionModel] with TreeEnsembleModel with Serializable

    :: Experimental :: Random Forest model for regression.

14. final class RandomForestRegressor extends Predictor[Vector, RandomForestRegressor, RandomForestRegressionModel] with RandomForestParams with TreeRegressorParams

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

15. abstract class RegressionModel[FeaturesType, M <: RegressionModel[FeaturesType, M]] extends PredictionModel[FeaturesType, M] with PredictorParams

    :: DeveloperApi ::