Package org.apache.spark.ml.regression

Class Summary

Class	Description
AFTAggregator	AFTAggregator computes the gradient and loss for a AFT loss function, as used in AFT survival regression for samples in sparse or dense vector in an online fashion.
AFTCostFun	AFTCostFun implements Breeze's DiffFunction[T] for AFT cost.
AFTSurvivalRegression	:: Experimental :: Fit a parametric survival regression model named accelerated failure time (AFT) model (see Accelerated failure time model (Wikipedia)) based on the Weibull distribution of the survival time.
AFTSurvivalRegressionModel	:: Experimental :: Model produced by AFTSurvivalRegression.
DecisionTreeRegressionModel	Decision tree (Wikipedia) model for regression.
DecisionTreeRegressor	Decision tree learning algorithm for regression.
GBTRegressionModel	Gradient-Boosted Trees (GBTs) model for regression.
GBTRegressor	Gradient-Boosted Trees (GBTs) learning algorithm for regression.
GeneralizedLinearRegression	:: Experimental ::
GeneralizedLinearRegression.Binomial$	Binomial exponential family distribution.
GeneralizedLinearRegression.CLogLog$
GeneralizedLinearRegression.Family$
GeneralizedLinearRegression.FamilyAndLink$
GeneralizedLinearRegression.Gamma$	Gamma exponential family distribution.
GeneralizedLinearRegression.Gaussian$	Gaussian exponential family distribution.
GeneralizedLinearRegression.Identity$
GeneralizedLinearRegression.Inverse$
GeneralizedLinearRegression.Link$
GeneralizedLinearRegression.Log$
GeneralizedLinearRegression.Logit$
GeneralizedLinearRegression.Poisson$	Poisson exponential family distribution.
GeneralizedLinearRegression.Probit$
GeneralizedLinearRegression.Sqrt$
GeneralizedLinearRegression.Tweedie$
GeneralizedLinearRegressionModel	:: Experimental :: Model produced by GeneralizedLinearRegression.
GeneralizedLinearRegressionSummary	:: Experimental :: Summary of GeneralizedLinearRegression model and predictions.
GeneralizedLinearRegressionTrainingSummary	:: Experimental :: Summary of GeneralizedLinearRegression fitting and model.
IsotonicRegression	Isotonic regression.
IsotonicRegressionModel	Model fitted by IsotonicRegression.
LinearRegression	Linear regression.
LinearRegressionModel	Model produced by LinearRegression.
LinearRegressionSummary	:: Experimental :: Linear regression results evaluated on a dataset.
LinearRegressionTrainingSummary	:: Experimental :: Linear regression training results.
RandomForestRegressionModel	Random Forest model for regression.
RandomForestRegressor	Random Forest learning algorithm for regression.
RegressionModel<FeaturesType,M extends RegressionModel<FeaturesType,M>>	:: DeveloperApi ::