基于混淆矩阵的自适应纠错输出编码多类分类方法

摘要

It is an effective way to transform multiclass into binary by using error-correcting output code (ECOC) as a decomposing frame,in which the research of encoding based on data especially attracts attentions.An encoding method for adaptively constructing ECOC is proposed.To achieve this goal,the relativity between each pair of patterns is achieved with the help of confusion matrixes.Then abiding by the Fisher's principle,the most favorable combination of patterns for classifying is obtained,and a binary partition based on the way of pattern combination and a data driven coding matrix are gotten.Experimental results on UCI datasets and three kinds of HRRP datasets show that the proposed scheme provides a better performance and robustness of classification than the classical encoding strategies.%利用纠错输出编码(error-correcting output code,ECOC)作为分解框架,把多类问题转化为二类问题进行求解,是目前解决多类分类的有效手段之一.如何构造基于数据的分解框架是应用此类方法的重点.为此,提出一种自适应纠错输出编码构造方法,利用混淆矩阵计算多类问题中各类别的相关性,基于Fisher准则找出最有利于分类的类别组合,最后根据组合方案构建类别的二类划分并最终形成输出编码.实验中分别对UCI数据集和3种一维距离像数据集进行测试,通过与几种经典的编码方法比较,结果表明该编码方法可以显著提高分类器的性能和稳健性.