{"title":"逆近似推理:最大熵","authors":"E. Eslami, J. Buckley","doi":"10.1109/ISUMA.1995.527781","DOIUrl":null,"url":null,"abstract":"We consider the problem of given the conclusion of a fuzzy rule, find in some sense the \"best\" data (input) that will produce the given conclusion. In this paper we investigate the use of the principle of maximum entropy to solve this problem.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Inverse approximate reasoning: maximize entropy\",\"authors\":\"E. Eslami, J. Buckley\",\"doi\":\"10.1109/ISUMA.1995.527781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider the problem of given the conclusion of a fuzzy rule, find in some sense the \\\"best\\\" data (input) that will produce the given conclusion. In this paper we investigate the use of the principle of maximum entropy to solve this problem.\",\"PeriodicalId\":298915,\"journal\":{\"name\":\"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISUMA.1995.527781\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISUMA.1995.527781","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We consider the problem of given the conclusion of a fuzzy rule, find in some sense the "best" data (input) that will produce the given conclusion. In this paper we investigate the use of the principle of maximum entropy to solve this problem.
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