计算机应用研究2011，Vol.28Issue(8)：2848-2851,2882,5.DOI:10.3969/j.issn.1001-3695.2011.08.013
一种改进的可能模糊聚类算法
Improved possibilistic fuzzy clustering algorithm
摘要
Abstract
After analyzing popular clustering algorithms, such as FCM, PCM, IPCM and PFCM, they are sensitive to outliers faults in noisy environments. This paper proposed a new algorithm called sample weighted improved possibilistic fuzzy clustering method ( SWPFCM). Based on combination sample weighting and a suitable for noise environment of initialization clustering center method, SWPFCM was less sensitive to outliers. The experimental results with data sets show that SWIPCM algorithm can deal with the amount of noise data, and produce less clustering time and better clustering accuracy.关键词
样本加权/模糊聚类/可能模糊聚类Key words
sample weighted/ fuzzy clustering/ possibilistic fuzzy clustering分类
信息技术与安全科学引用本文复制引用
张辰,夏士雄,刘兵..一种改进的可能模糊聚类算法[J].计算机应用研究,2011,28(8):2848-2851,2882,5.基金项目
国家教育部科学技术研究重点资助项目(108063) （108063）
