Uses of Enum Class
org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType

Packages that use XGBoostRegressionTrainer.RegressionType

Package	Description
org.tribuo.regression.xgboost	Provides an interface to XGBoost for regression problems.

Uses of XGBoostRegressionTrainer.RegressionType in org.tribuo.regression.xgboost

Subclasses with type arguments of type XGBoostRegressionTrainer.RegressionType in org.tribuo.regression.xgboost

Modifier and Type	Class	Description
static enum	XGBoostRegressionTrainer.RegressionType	Types of regression loss.

Fields in org.tribuo.regression.xgboost declared as XGBoostRegressionTrainer.RegressionType

Modifier and Type	Field	Description
XGBoostRegressionTrainer.RegressionType	TrainTest.XGBoostOptions.rType	Regression type to use.
XGBoostRegressionTrainer.RegressionType	XGBoostOptions.rType	Regression type to use.

Methods in org.tribuo.regression.xgboost that return XGBoostRegressionTrainer.RegressionType

Modifier and Type	Method	Description
static XGBoostRegressionTrainer.RegressionType	XGBoostRegressionTrainer.RegressionType.valueOf(String name)	Returns the enum constant of this class with the specified name.
static XGBoostRegressionTrainer.RegressionType[]	XGBoostRegressionTrainer.RegressionType.values()	Returns an array containing the constants of this enum class, in the order they are declared.

Constructors in org.tribuo.regression.xgboost with parameters of type XGBoostRegressionTrainer.RegressionType

Modifier	Constructor	Description
	XGBoostRegressionTrainer(XGBoostTrainer.BoosterType boosterType, XGBoostTrainer.TreeMethod treeMethod, XGBoostRegressionTrainer.RegressionType rType, int numTrees, double eta, double gamma, int maxDepth, double minChildWeight, double subsample, double featureSubsample, double lambda, double alpha, int nThread, XGBoostTrainer.LoggingVerbosity verbosity, long seed)	Create an XGBoost trainer.
	XGBoostRegressionTrainer(XGBoostRegressionTrainer.RegressionType rType, int numTrees)	Creates an XGBoostRegressionTrainer using the default parameters, the supplied loss and the supplied number of trees.
	XGBoostRegressionTrainer(XGBoostRegressionTrainer.RegressionType rType, int numTrees, double eta, double gamma, int maxDepth, double minChildWeight, double subsample, double featureSubsample, double lambda, double alpha, int nThread, boolean silent, long seed)	Create an XGBoost trainer.
	XGBoostRegressionTrainer(XGBoostRegressionTrainer.RegressionType rType, int numTrees, int numThreads, boolean silent)	Creates an XGBoostRegressionTrainer using the default parameters with the supplied loss, number of trees, number of threads, and logging level.
	XGBoostRegressionTrainer(XGBoostRegressionTrainer.RegressionType rType, int numTrees, Map<String,Object> parameters)	This gives direct access to the XGBoost parameter map.