期刊
KNOWLEDGE-BASED SYSTEMS
卷 119, 期 -, 页码 32-43出版社
ELSEVIER
DOI: 10.1016/j.knosys.2016.12.004
关键词
Aggregation functions; Choquet integral; Copula; t-norm; Overlap function; Fuzzy rule-based classification systems; Fuzzy reasoning method
资金
- Brazilian National Counsel of Technological and Scientific Development CNPq [232827/2014-1, 233950/2014-1, 481283/2013-7, 306970/2013-9, 307681/2012-2]
- Spanish Ministry of Science and Technology [TIN2016-77356-P]
This paper introduces the concept of Choquet-like Copula-based aggregation function (CC-integral) and its application in fuzzy rule-based classification systems. The standard Choquet integral is expanded by distributing the product operation. Then, the product operation is generalized by a copula. Unlike the generalization of the Choquet integral by t-norms using its standard form (i.e., without distributing the product operator), which results in a pre-aggregation function, the CC-integral satisfies all the conditions required for an aggregation function. We build some examples of CC-integrals considering different examples of copulas, including t-norms, overlap functions and copulas that are neither t-norms nor overlap functions. We show that the CC-integral based on the minimum t-norm, when applied in fuzzy rule based classification systems, obtains a performance that is, with a high level of confidence, better than that which adopts the winning rule (maximum). We concluded that the behavior of CC-integral is similar to the best Choquet-like pre-aggregation function. Consequently, the CC-integrals introduced in this paper can enlarge the scope of the applications by offering new possibilities for defining fuzzy reasoning methods with a similar gain in performance. (C) 2016 Elsevier B.V. All rights reserved.
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