jsat.classifiers.linear

Enum StochasticSTLinearL1.Loss

java.lang.Object

java.lang.Enum<StochasticSTLinearL1.Loss>

jsat.classifiers.linear.StochasticSTLinearL1.Loss

All Implemented Interfaces:

Serializable, Comparable<StochasticSTLinearL1.Loss>

Enclosing class:

StochasticSTLinearL1

public static enum StochasticSTLinearL1.Loss
extends Enum<StochasticSTLinearL1.Loss>

Enum Constant Summary

Enum Constants

Enum Constant and Description
LOG
SQUARED

Method Summary

Modifier and Type	Method and Description
abstract double	beta() Returns an upper bound on the 2nd derivative for classification
abstract CategoricalResults	classify(double a) The categorical results for a classification problem
abstract double	deriv(double a, double y) Returns the value of the derivative of the loss function
abstract double	loss(double a, double y) Returns the loss on the prediction
abstract double	regress(double a) The output value result for a regression problem
static StochasticSTLinearL1.Loss	valueOf(String name) Returns the enum constant of this type with the specified name.
static StochasticSTLinearL1.Loss[]	values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods inherited from class java.lang.Enum

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

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Enum Constant Detail

SQUARED

public static final StochasticSTLinearL1.Loss SQUARED

LOG

public static final StochasticSTLinearL1.Loss LOG

Method Detail

values

public static StochasticSTLinearL1.Loss[] values()

Returns an array containing the constants of this enum type, in the order they are declared. This method may be used to iterate over the constants as follows:

for (StochasticSTLinearL1.Loss c : StochasticSTLinearL1.Loss.values())
    System.out.println(c);

Returns:

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

valueOf

public static StochasticSTLinearL1.Loss valueOf(String name)

Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (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 type has no constant with the specified name

NullPointerException - if the argument is null

loss

public abstract double loss(double a,
                            double y)

Returns the loss on the prediction

Parameters:

a - the predicted value

y - the target value

Returns:

the loss

deriv

public abstract double deriv(double a,
                             double y)

Returns the value of the derivative of the loss function

Parameters:

a - the predicted value

y - the target value

Returns:

the derivative of the loss

beta

public abstract double beta()

Returns an upper bound on the 2nd derivative for classification

Returns:

an upper bound on the 2nd derivative for classification

classify

public abstract CategoricalResults classify(double a)

The categorical results for a classification problem

Parameters:

a - the dot product of the weight vector and an input

Returns:

the binary problem classification results

regress

public abstract double regress(double a)

The output value result for a regression problem

Parameters:

a - the dot product of the weight vector and an input

Returns:

the final regression output