{"title":"用质量分配理论获得模糊集-与插值的一致性","authors":"A. Ralescu, S. Visa","doi":"10.1109/NAFIPS.2007.383879","DOIUrl":null,"url":null,"abstract":"The problem of data summarization as fuzzy sets from frequency distributions is presented. The approach makes use of the mass assignment theory as a framework for unification of fuzzy sets and probability distributions. The approach is consistent with the interpolation of the membership function needed to infer membership degrees for data points previously not seen.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Obtaining Fuzzy Sets using Mass Assignment Theory - Consistency with Interpolation -\",\"authors\":\"A. Ralescu, S. Visa\",\"doi\":\"10.1109/NAFIPS.2007.383879\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of data summarization as fuzzy sets from frequency distributions is presented. The approach makes use of the mass assignment theory as a framework for unification of fuzzy sets and probability distributions. The approach is consistent with the interpolation of the membership function needed to infer membership degrees for data points previously not seen.\",\"PeriodicalId\":292853,\"journal\":{\"name\":\"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2007.383879\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2007.383879","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Obtaining Fuzzy Sets using Mass Assignment Theory - Consistency with Interpolation -
The problem of data summarization as fuzzy sets from frequency distributions is presented. The approach makes use of the mass assignment theory as a framework for unification of fuzzy sets and probability distributions. The approach is consistent with the interpolation of the membership function needed to infer membership degrees for data points previously not seen.