摘要
针对传统核匹配追踪(kernel matching pursuit,KMP)学习机只能解决二类分类问题的不足,结合纠错输出编码(error-correcting output codes,ECOC)的思想,提出了一种基于Hadamard纠错码的核匹配追踪多类分类方法。该算法通过Hadmard纠错码将核匹配追踪算法推广到多类分类领域,并利用纠错码本身具备的纠错能力提高了分类器的泛化性能。实验中分别对UCI数据集和3种典型空天目标的高分辨一维距离像(high resolution range profile,HRRP)数据集进行测试,通过与2种经典的编码方法进行比较,结果表明该编码方法可以显著提高分类器的性能和鲁棒性。
Since the classical kernel matching pursuit （KMP）learner can only address the binary classification problems,a KMP based on Hadamard correct codes is proposed,borowing the idea of error-correcting output codes （ECOC）.This algorithm can be extended to multi-class classification through Hadamard correct codes.Moreover,the correcting ability of the correct codes can enhance the generation capability of the classifier.The illustrative experiments implemented on UCI datasets and three kinds of aero target high resolution range profile （HRRP）data set demonstrate that the proposed algorithm outperforms two other coding methods in both classification performance and robust ness.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2015年第10期2228-2233,共6页
Systems Engineering and Electronics
基金
国家自然科学基金(61272011
61309022)
陕西省自然科学青年基金项目(2013JQ8031)资助课题
