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发表时间：2012-01-01

发表刊物：大连理工大学学报

所属单位：电子信息与电气工程学部

卷号：52

期号：5

页面范围：749-754

ISSN号：1000-8608

摘要：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.

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