Hits:

Indexed by:会议论文

Date of Publication:2015-08-26

Included Journals:EI、CPCI-S、Scopus

Volume:1

Page Number:407-410

Key Words:fuzzy clustering; incomplete data; attribute weighted; statistcal imputation

Abstract:The problem of missing data is frequently encountered in real world applications. In this paper, an attribute weighted fuzzy c-means algorithm for incomplete data sets is presented. The statistical representation proposed in our previous work is used here to impute the missing attribute values, and attribute weighting is involved to emphasize the contribution of important attributes. Experimental results indicate that the proposed approach has good clustering performance.