计算机应用研究2017，Vol.34Issue(12)：3681-3684,3688,5.DOI:10.3969/j.issn.1001-3695.2017.12.036
基于类间判别的矩阵学习机
Matrixized learning machine with between-class discrimination
摘要
Abstract
Matrix-pattern-oriented classifier design(MatCD) might neglect the prior discriminant information among different classes.To overcome this shortcoming,this paper designed a new learning framework of MatCD.Firstly,it used K-means to cluster every class,and then maximized the distance among the cluster centers of different classes.Lastly,it adoped the new regularization term RBc into MatCD.The experimental results show that the new learning framework of MatCD improves the classification of MatCD.Moreover,it also indicates that RBC is effectively.关键词
面向矩阵模式的分类设计/分簇/正则化项学习/模式识别Key words
matrix-pattern-oriented classifier design/clustering/regularization term learning/pattern recognition分类
信息技术与安全科学引用本文复制引用
张国威,王喆..基于类间判别的矩阵学习机[J].计算机应用研究,2017,34(12):3681-3684,3688,5.基金项目
国家自然科学基金资助项目(61672227,61272198) （61672227,61272198）
上海市教委科研创新重点资助项目(14ZZ054) （14ZZ054）
