{"title":"Atanassov直觉模糊集的三项属性描述作为属性选择的基础","authors":"E. Szmidt, J. Kacprzyk, Paweł Bujnowski","doi":"10.1109/FUZZ45933.2021.9494599","DOIUrl":null,"url":null,"abstract":"We propose here a new proposal for attribute selection in the models expressed by the intuitionistic fuzzy sets. We further develop our previous paper in which the approach was already extended and the first computational tests were performed, i.e., the method was compared with the Principal Component Analysis (PCA). Here we test how the method behaves in comparison with the selection while using the Gain Ratio. We consider classification problems and try to reduce the number of attributes to not obtain substantially worse results.","PeriodicalId":151289,"journal":{"name":"2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Three term attribute description of Atanassov's Intuitionistic Fuzzy Sets as a basis of attribute selection\",\"authors\":\"E. Szmidt, J. Kacprzyk, Paweł Bujnowski\",\"doi\":\"10.1109/FUZZ45933.2021.9494599\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose here a new proposal for attribute selection in the models expressed by the intuitionistic fuzzy sets. We further develop our previous paper in which the approach was already extended and the first computational tests were performed, i.e., the method was compared with the Principal Component Analysis (PCA). Here we test how the method behaves in comparison with the selection while using the Gain Ratio. We consider classification problems and try to reduce the number of attributes to not obtain substantially worse results.\",\"PeriodicalId\":151289,\"journal\":{\"name\":\"2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FUZZ45933.2021.9494599\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZ45933.2021.9494599","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Three term attribute description of Atanassov's Intuitionistic Fuzzy Sets as a basis of attribute selection
We propose here a new proposal for attribute selection in the models expressed by the intuitionistic fuzzy sets. We further develop our previous paper in which the approach was already extended and the first computational tests were performed, i.e., the method was compared with the Principal Component Analysis (PCA). Here we test how the method behaves in comparison with the selection while using the Gain Ratio. We consider classification problems and try to reduce the number of attributes to not obtain substantially worse results.