package regression

  1. Public
  2. All

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 ( 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 ::

Value Members

  1. object AFTSurvivalRegression extends DefaultParamsReadable[AFTSurvivalRegression] with Serializable

    @Since( "1.6.0" )
  2. object AFTSurvivalRegressionModel extends MLReadable[AFTSurvivalRegressionModel] with Serializable

    @Since( "1.6.0" )
  3. object DecisionTreeRegressor extends Serializable

    @Since( "1.4.0" ) @Experimental()
  4. object GBTRegressor extends Serializable

    @Since( "1.4.0" ) @Experimental()
  5. object IsotonicRegression extends DefaultParamsReadable[IsotonicRegression] with Serializable

    @Since( "1.6.0" )
  6. object IsotonicRegressionModel extends MLReadable[IsotonicRegressionModel] with Serializable

    @Since( "1.6.0" )
  7. object LinearRegression extends DefaultParamsReadable[LinearRegression] with Serializable

    @Since( "1.6.0" )
  8. object LinearRegressionModel extends MLReadable[LinearRegressionModel] with Serializable

    @Since( "1.6.0" )
  9. object RandomForestRegressor extends Serializable

    @Since( "1.4.0" ) @Experimental()