Interface  Description 

AFTSurvivalRegressionParams 
Params for accelerated failure time (AFT) regression.

FactorizationMachines  
FactorizationMachinesParams 
Params for Factorization Machines

FMRegressorParams 
Params for FMRegressor

GeneralizedLinearRegressionBase 
Params for Generalized Linear Regression.

IsotonicRegressionBase 
Params for isotonic regression.

LinearRegressionParams 
Params for linear regression.

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 
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 
Model produced by
AFTSurvivalRegression . 
DecisionTreeRegressionModel 
Decision tree (Wikipedia) model for regression.

DecisionTreeRegressor 
Decision tree
learning algorithm for regression.

FMRegressionModel 
Model produced by
FMRegressor . 
FMRegressor 
Factorization Machines learning algorithm for regression.

GBTRegressionModel 
GradientBoosted Trees (GBTs)
model for regression.

GBTRegressor 
GradientBoosted Trees (GBTs)
learning algorithm for regression.

GeneralizedLinearRegression 
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).

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 
Model produced by
GeneralizedLinearRegression . 
GeneralizedLinearRegressionSummary 
Summary of
GeneralizedLinearRegression model and predictions. 
GeneralizedLinearRegressionTrainingSummary 
Summary of
GeneralizedLinearRegression fitting and model. 
InternalLinearRegressionModelWriter 
A writer for LinearRegression that handles the "internal" (or default) format

IsotonicRegression 
Isotonic regression.

IsotonicRegressionModel 
Model fitted by IsotonicRegression.

LinearRegression 
Linear regression.

LinearRegressionModel 
Model produced by
LinearRegression . 
LinearRegressionSummary 
Linear regression results evaluated on a dataset.

LinearRegressionTrainingSummary 
Linear regression training results.

PMMLLinearRegressionModelWriter 
A writer for LinearRegression that handles the "pmml" format

RandomForestRegressionModel 
Random Forest model for regression.

RandomForestRegressor 
Random Forest
learning algorithm for regression.

RegressionModel<FeaturesType,M extends RegressionModel<FeaturesType,M>> 
Model produced by a
Regressor . 
Regressor<FeaturesType,Learner extends Regressor<FeaturesType,Learner,M>,M extends RegressionModel<FeaturesType,M>> 
Singlelabel regression
