Hits:

Date of Publication:2022-10-10

Journal:大连理工大学学报

Affiliation of Author(s):电子信息与电气工程学部

Volume:52

Issue:5

Page Number:749-754

ISSN No.:1000-8608

Abstract:In view of the problem that the existing algorithms for incomplete data
   fuzzy clustering generally view each dimensional attribute as equally
   important in contribution of clustering,an attribute weighted fuzzy
   c-means algorithm for incomplete data clustering is proposed.In the
   proposed algorithm,the important degree of each dimensional attribute is
   evaluated by the ReliefF algorithm and combined into fuzzy clustering by
   weighted Euclidean distance,and missing attribute values,membership and
   clustering centers can be obtained simultaneously.The experimental
   results show that the proposed algorithm can emphasize the important
   attributes in clustering,and better clustering results can be obtained.

Note:新增回溯数据