dragon.ir.classification.multiclass

Interface CodeMatrix

All Known Implementing Classes:

AbstractCodeMatrix, AllPairCodeMatrix, OVACodeMatrix

public interface CodeMatrix

Code Matrix Interface

The code matrix handle the problem of how to build a set of binary classifiers for multi-class classification. A row of the code matrix corresponds to a class label and the column a binary classsifer. The cell value at row i and column j can be -1, 0, or +1. -1 means the training examples of category i will be used as negative examples for the j-th binary classifier. +1 * means the training examples of category i will be used as positive examples for the j-th binary classifier. O means not used for training.

More details can be found in the following paper:
Allwein, E.L., Schapire, R.E., and Singer, Y., Reducing multiclass to binary: A unifying approach for margin classifiers, Journal of Machine Learning Research, 1:113:C141, 2000.

Copyright: Copyright (c) 2005

Company: IST, Drexel University

Version:

1.0

Author:

Davis Zhou

Method Summary

Modifier and Type	Method and Description
int	getClassifierNum() Gets the number of binary classifiers
int	getClassNum() Gets the number of categories
int	getCode(int classIndex, int classifierIndex) Gets the code value for specified category and binary classifier
void	setClassNum(int classNum) Sets the number of categories

Method Detail

getClassNum

int getClassNum()

Gets the number of categories

Returns:

the number of categories

setClassNum

void setClassNum(int classNum)

Sets the number of categories

Parameters:

classNum - the number of categories

getClassifierNum

int getClassifierNum()

Gets the number of binary classifiers

Returns:

the number of binary classifiers

getCode

int getCode(int classIndex,
            int classifierIndex)

Gets the code value for specified category and binary classifier

Parameters:

classIndex - the index of the category

classifierIndex - the index of the binary classifier

Returns:

-1, 0, +1. -1 means the training examples of category i will be used as negative examples for the j-th binary classifier. +1 means the training examples of category i will be used as positive examples for the j-th binary classifier. O means not used for training.