Y. W. Choong, Lisa Di-Jorio, Anne Laurent, D. Laurent, M. Teisseire
{"title":"CBGP:基于渐进模式的分类","authors":"Y. W. Choong, Lisa Di-Jorio, Anne Laurent, D. Laurent, M. Teisseire","doi":"10.1109/SoCPaR.2009.15","DOIUrl":null,"url":null,"abstract":"In this paper, we address the issue of mining gradual classification rules. In general, gradual patterns refer to regularities such as ``The older a person, the higher his salary''. Such patterns are extensively and successfully used in command-based systems, especially in fuzzy command applications. However, in such applications, gradual patterns are supposed to be known and/or provided by an expert, which is not always realistic in practice. In this work, we aim at mining from a given training dataset such gradual patterns for the generation of gradual classification rules. Gradual classification rules thus refer to rules where the antecedent is a gradual pattern and the conclusion is a class value.","PeriodicalId":284743,"journal":{"name":"2009 International Conference of Soft Computing and Pattern Recognition","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"CBGP: Classification Based on Gradual Patterns\",\"authors\":\"Y. W. Choong, Lisa Di-Jorio, Anne Laurent, D. Laurent, M. Teisseire\",\"doi\":\"10.1109/SoCPaR.2009.15\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we address the issue of mining gradual classification rules. In general, gradual patterns refer to regularities such as ``The older a person, the higher his salary''. Such patterns are extensively and successfully used in command-based systems, especially in fuzzy command applications. However, in such applications, gradual patterns are supposed to be known and/or provided by an expert, which is not always realistic in practice. In this work, we aim at mining from a given training dataset such gradual patterns for the generation of gradual classification rules. Gradual classification rules thus refer to rules where the antecedent is a gradual pattern and the conclusion is a class value.\",\"PeriodicalId\":284743,\"journal\":{\"name\":\"2009 International Conference of Soft Computing and Pattern Recognition\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference of Soft Computing and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SoCPaR.2009.15\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference of Soft Computing and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SoCPaR.2009.15","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we address the issue of mining gradual classification rules. In general, gradual patterns refer to regularities such as ``The older a person, the higher his salary''. Such patterns are extensively and successfully used in command-based systems, especially in fuzzy command applications. However, in such applications, gradual patterns are supposed to be known and/or provided by an expert, which is not always realistic in practice. In this work, we aim at mining from a given training dataset such gradual patterns for the generation of gradual classification rules. Gradual classification rules thus refer to rules where the antecedent is a gradual pattern and the conclusion is a class value.