D. Paternain, A. Jurio, H. Bustince, M. J. Campión, I. Perfilieva, R. Mesiar
{"title":"A construction method of internal functions","authors":"D. Paternain, A. Jurio, H. Bustince, M. J. Campión, I. Perfilieva, R. Mesiar","doi":"10.1109/FUZZ-IEEE.2017.8015640","DOIUrl":null,"url":null,"abstract":"In this work we investigate a new family of fusion functions called internal fusion functions. The main characteristic of these functions is the fact that the output always corresponds to some of the given inputs. We propose a construction method and we study whether internal functions constructed in this way also satisfy properties of aggregation functions Finally, we apply internal functions in an example of a multi-class problem, where a set of matrices must be combine into a single representative collective matrix in order to obtain better classification rates.","PeriodicalId":408343,"journal":{"name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZ-IEEE.2017.8015640","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this work we investigate a new family of fusion functions called internal fusion functions. The main characteristic of these functions is the fact that the output always corresponds to some of the given inputs. We propose a construction method and we study whether internal functions constructed in this way also satisfy properties of aggregation functions Finally, we apply internal functions in an example of a multi-class problem, where a set of matrices must be combine into a single representative collective matrix in order to obtain better classification rates.