一种新的模糊聚类有效性指标

doi:10.3969/j.issn.1006-2475.2014.07.003

计算机与现代化

一种新的模糊聚类有效性指标

（阿坝师范高等专科学校基础教育系，四川汶川 623002）

收稿日期:2014-04-16 出版日期:2014-07-16 发布日期:2014-07-17
作者简介:汤官宝(1986-)，男，河南信阳人，阿坝师范高等专科学校基础教育系助教，硕士，研究方向：人工智能，模式识别。
基金资助:
阿坝师范高等专科学校青年科研基金资助项目（ASC11-17）

A Novel Validity Index for Fuzzy Clustering

(Department of Elementary Education, Aba Teachers College, Wenchuan 623002, China)

Received:2014-04-16 Online:2014-07-16 Published:2014-07-17

摘要/Abstract

摘要： 结合模糊聚类的类内紧致性和类间分离性信息，提出一种新的模糊聚类有效性指标。该指标能够确定由模糊C-均值算法（FCM）所得模糊划分的最优划分和最佳聚类数。在1个人造数据集和4个真实数据集上进行对比实验，结果表明该指标性能的优越性。

关键词: 模糊聚类, 有效性指标, 模糊C-均值算法

Abstract: Combining compactness and separation information of fuzzy clustering, this paper proposes a novel validity index for clustering. This index can determine optimal partition and optimal number of clusters for fuzzy partitions obtained from the fuzzy C-means algorithm (FCM). Comparison experiment is done in one synthetic data set and four real datasets, and the results prove that this index has superior effectiveness.

Key words: fuzzy clustering, validity index, fuzzy C-means algorithm

中图分类号:

TP181

汤官宝. 一种新的模糊聚类有效性指标[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2014.07.003.

TANG Guan-bao. A Novel Validity Index for Fuzzy Clustering[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2014.07.003.

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一种新的模糊聚类有效性指标

A Novel Validity Index for Fuzzy Clustering

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