Uses of Interface
smile.regression.Regression

Packages that use Regression

Package	Description
smile.regression	Regression analysis.
smile.validation	Model validation.

Uses of Regression in smile.regression

Subinterfaces of Regression in smile.regression

Modifier and Type	Interface and Description
interface	OnlineRegression<T> Regression model with online learning capability.

Classes in smile.regression that implement Regression

Modifier and Type	Class and Description
class	GaussianProcessRegression<T> Gaussian Process for Regression.
class	GradientTreeBoost Gradient boosting for regression.
class	LASSO Least absolute shrinkage and selection operator.
class	OLS Ordinary least squares.
class	RandomForest Random forest for regression.
class	RBFNetwork<T> Radial basis function network.
class	RegressionTree Decision tree for regression.
class	RidgeRegression Ridge Regression.
class	SVR<T> Support vector regression.

Methods in smile.regression that return Regression

Modifier and Type	Method and Description
abstract Regression<T>	RegressionTrainer.train(T[] x, double[] y) Learns a regression model with given training data.

Uses of Regression in smile.validation

Methods in smile.validation with parameters of type Regression

Modifier and Type	Method and Description
static <T> double	Validation.test(Regression<T> regression, T[] x, double[] y) Tests a regression model on a validation set.
static <T> double	Validation.test(Regression<T> regression, T[] x, double[] y, RegressionMeasure measure) Tests a regression model on a validation set.
static <T> double[]	Validation.test(Regression<T> regression, T[] x, double[] y, RegressionMeasure[] measures) Tests a regression model on a validation set.