Package org.tribuo.regression.xgboost

Enum Class XGBoostRegressionTrainer.RegressionType

java.lang.Object

java.lang.Enum<XGBoostRegressionTrainer.RegressionType>

org.tribuo.regression.xgboost.XGBoostRegressionTrainer.RegressionType

All Implemented Interfaces:

Serializable, Comparable<XGBoostRegressionTrainer.RegressionType>, Constable

Enclosing class:

XGBoostRegressionTrainer

public static enum XGBoostRegressionTrainer.RegressionType
extends Enum<XGBoostRegressionTrainer.RegressionType>

Types of regression loss.

Nested Class Summary

Nested classes/interfaces inherited from class java.lang.Enum

Enum.EnumDesc<E extends Enum<E>>

Enum Constant Summary

Enum Constants

Enum Constant	Description
GAMMA	Gamma loss function.
LINEAR	Squared error loss function.
PSEUDOHUBER	Pseudo-huber loss, a differentiable approximation to absolute error
TWEEDIE	Tweedie loss function.

Field Summary

Fields

Modifier and Type	Field	Description
final String	paramName	The parameter name used by the XGBoost native library.

Method Summary

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

Methods inherited from class java.lang.Enum

clone, compareTo, describeConstable, equals, finalize, getDeclaringClass, hashCode, name, ordinal, toString, valueOf

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Enum Constant Details

LINEAR

public static final XGBoostRegressionTrainer.RegressionType LINEAR

Squared error loss function.

GAMMA

public static final XGBoostRegressionTrainer.RegressionType GAMMA

Gamma loss function.

TWEEDIE

public static final XGBoostRegressionTrainer.RegressionType TWEEDIE

Tweedie loss function.

PSEUDOHUBER

public static final XGBoostRegressionTrainer.RegressionType PSEUDOHUBER

Pseudo-huber loss, a differentiable approximation to absolute error

Field Details

paramName

public final String paramName

The parameter name used by the XGBoost native library.

Method Details

values

public static XGBoostRegressionTrainer.RegressionType[] values()

Returns an array containing the constants of this enum class, in the order they are declared.

Returns:

an array containing the constants of this enum class, in the order they are declared

valueOf

public static XGBoostRegressionTrainer.RegressionType valueOf(String name)

Returns the enum constant of this class with the specified name. The string must match exactly an identifier used to declare an enum constant in this class. (Extraneous whitespace characters are not permitted.)

Parameters:

name - the name of the enum constant to be returned.

Returns:

the enum constant with the specified name

Throws:

IllegalArgumentException - if this enum class has no constant with the specified name

NullPointerException - if the argument is null