| 基于改进属性约简的粗核聚类算法 |
| |
| 引用本文： | 徐丽,丁世飞,郭锋锋.基于改进属性约简的粗核聚类算法[J].广西师范大学学报(自然科学版),2011,29(3):105-109. |
| |
| 作者姓名： | 徐丽 丁世飞 郭锋锋 |
| |
| 作者单位： | 1. 中国矿业大学计算机科学与技术学院,江苏徐州,221116
2. 中国矿业大学计算机科学与技术学院,江苏徐州221116;中国科学院计算技术研究所智能信息处理重点实验室,北京100080 |
| |
| 基金项目： | 国家自然科学基金资助项目(60975039); 江苏省基础研究计划(自然科学基金)资助项目(BK2009093) |
| |
| 摘 要： | 核聚类算法是一种能够处理样本间差异微弱的有效聚类算法.以粗糙集理论为基础,将基于属性重要度的属性约简算法应用到核聚类算法中,提出一种新的聚类改进算法,由此可以得到高准确率低复杂度的良好结果.该算法在使用核函数对样本优化前,首先用基于属性重要度的约简算法对样本属性进行处理,同时引入信息熵来改进约简算法,从而删除冗余属性得...
|
| 关 键 词： | 粗糙集 属性约简 属性重要度 信息熵 核聚类 |
A Rough Kernel Clustering Algorithm Based on Improved Attribute Reduction |
| |
| XU Li,DING Shi-fei,GUO Feng-feng.A Rough Kernel Clustering Algorithm Based on Improved Attribute Reduction[J].Journal of Guangxi Normal University(Natural Science Edition),2011,29(3):105-109. |
| |
| Authors: | XU Li DING Shi-fei GUO Feng-feng |
| |
| Institution: | XU Li1,DING Shi-fei1,2,GUO Feng-feng1(1.School of Computer Science and Technology,China University of Mining and Technology,Xuzhou Jiangsu 221116,China,2.Key Laboratory of Intelligent Information Processing,Institute of Computing Technology,ChineseAcademy of Science,Beijing 100080,China) |
| |
| Abstract: | Kernel clustering is an effective algorithm which can deal with samples that have weak differences.On the basis that of new improved attribute importance under the theory of rough set is applied to the kernel clustering algorithm.Before the samples are optimized by the kernel function,their properties is processed by the reduction algorithm which is based on the attribute importance.At the same time,Information Entropy is introduced to improve the reduction algorithm.So the redundant attributes are deleted ... |
| |
| Keywords: | rough set attribute reduction attribute importance information entropy kernel clustering |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
