A new nearest neighbor classification method based on fuzzy set theory and aggregation operators

作者：

Highlights：

• New Fuzzy Nearest Neighbor Classification Method, called Fuzzy Analogy Based Classification (FABC).

• Describing the domain features by fuzzy sets.

• Management of uncertainty and impreciseness in classification process by means of aggregation operators.

• Promising results of the new classifier and compared with advanced Fuzzy Nearest Neighbor Classifiers.

摘要

•New Fuzzy Nearest Neighbor Classification Method, called Fuzzy Analogy Based Classification (FABC).•Describing the domain features by fuzzy sets.•Management of uncertainty and impreciseness in classification process by means of aggregation operators.•Promising results of the new classifier and compared with advanced Fuzzy Nearest Neighbor Classifiers.

论文关键词：Nearest neighbor classification,Fuzzy set theory,Fuzzy analogy based classification,OWA operators,Quasi-arithmetic mean operators,Management of uncertainty and impreciseness

论文评审过程：Received 12 November 2015, Revised 6 March 2017, Accepted 7 March 2017, Available online 8 March 2017, Version of Record 17 March 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.03.019