文章基本信息

标题：On classification with missing data using rough-neuro-fuzzy systems
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作者：Robert K. Nowicki
期刊名称：International Journal of Applied Mathematics and Computer Science
电子版ISSN：2083-8492
出版年度：2010
卷号：20
期号：1
DOI：10.2478/v10006-010-0004-8
出版社：De Gruyter Open
摘要：The paper presents a new approach to fuzzy classification in the case of missing data. Rough-fuzzy sets are incorporated into logical type neuro-fuzzy structures and a rough-neuro-fuzzy classifier is derived. Theorems which allow determining the structure of the rough-neuro-fuzzy classifier are given. Several experiments illustrating the performance of the rough-neuro-fuzzy classifier working in the case of missing features are described
关键词：fuzzy sets; rough sets; neuro-fuzzy architectures; classification; missing data