jsat

Interface SimpleWeightVectorModel

All Known Subinterfaces:

SingleWeightVectorModel

All Known Implementing Classes:

ALMA2, AROW, BBR, DCD, DCDs, LinearBatch, LinearL1SCD, LinearSGD, LogisticRegression, LogisticRegressionDCD, MultipleLinearRegression, NewGLMNET, NHERD, PassiveAggressive, Pegasos, Perceptron, ROMMA, SCD, SCW, SMIDAS, SPA, STGD, StochasticMultinomialLogisticRegression, StochasticRidgeRegression, StochasticSTLinearL1

public interface SimpleWeightVectorModel

This interface is for multi-class classification problems where there may be K or K-1 weight vectors for K classes. For regression problems it is treated as K = 1 and there should be only one weight vector.

Author:

Edward Raff

Method Summary

Modifier and Type	Method and Description
double	getBias(int index) Returns the bias term used with the weight vector for the given class index.
Vec	getRawWeight(int index) Returns the raw weight vector associated with the given class index.
int	numWeightsVecs() Returns the number of weight vectors that can be returned.

Method Detail

getRawWeight

Vec getRawWeight(int index)

Returns the raw weight vector associated with the given class index. If the given class is an implicit zero vector, a ConstantVector object may be returned.
Do not alter the returned weight vector, as it will change the model's values.

If a regression problem, only index = 0 should be used

Parameters:

index - the class index to get the weight vector for

Returns:

the weight vector used for the specified class

getBias

double getBias(int index)

Returns the bias term used with the weight vector for the given class index. If the model does not support or was not trained with bias weights, 0 will be returned.

If a regression problem, only index = 0 should be used

Parameters:

index - the class index to get the weight vector for

Returns:

the bias term for the specified class

numWeightsVecs

int numWeightsVecs()

Returns the number of weight vectors that can be returned. For binary classification problems the value may be 1 if only a single weight vector's sign is used to determine the class. For multi-class problems, the weight vector count includes the implicit zero vector (if one is being used).

Returns:

the number of weight vectors for which getRawWeight(int) can be called.