Package org.apache.spark.ml.regression
package org.apache.spark.ml.regression

ClassDescriptionFit 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.Model produced by
AFTSurvivalRegression
.Params for accelerated failure time (AFT) regression.Decision tree (Wikipedia) model for regression.Decision tree learning algorithm for regression.Params for Factorization MachinesModel produced byFMRegressor
.Factorization Machines learning algorithm for regression.Params for FMRegressorGradientBoosted Trees (GBTs) model for regression.GradientBoosted Trees (GBTs) learning algorithm for regression.Fit a Generalized Linear Model (see Generalized linear model (Wikipedia)) specified by giving a symbolic description of the linear predictor (link function) and a description of the error distribution (family).Binomial exponential family distribution.Gamma exponential family distribution.Gaussian exponential family distribution.Poisson exponential family distribution.Params for Generalized Linear Regression.Model produced byGeneralizedLinearRegression
.Summary ofGeneralizedLinearRegression
model and predictions.Summary ofGeneralizedLinearRegression
fitting and model.A writer for LinearRegression that handles the "internal" (or default) formatIsotonic regression.Params for isotonic regression.Model fitted by IsotonicRegression.Linear regression.Model produced byLinearRegression
.Params for linear regression.Linear regression results evaluated on a dataset.Linear regression training results.A writer for LinearRegression that handles the "pmml" formatRandom Forest model for regression.Random Forest learning algorithm for regression.RegressionModel<FeaturesType,M extends RegressionModel<FeaturesType, M>> Model produced by aRegressor
.Regressor<FeaturesType,Learner extends Regressor<FeaturesType, Learner, M>, M extends RegressionModel<FeaturesType, M>> Singlelabel regression