{"title":"规则归纳的协同进化算法","authors":"P. Myszkowski","doi":"10.1109/IMCSIT.2010.5679728","DOIUrl":null,"url":null,"abstract":"This paper describes our last research results in the field of evolutionary algorithms for rule extraction applied to classification (and image annotation). We focus on the data mining classification task and we propose evolutionary algorithm for rule extraction. Presented approach is based on binary classical genetic algorithm with representation of `if-then' rules and we propose two specialized genetic operators. We want to show that some search space reduction techniques make possible to get solution comparable to others from literature. To present our method ability of discovering the set of rules with high F-score we tested our approach on four benchmark datasets and ImageCLEF competition dataset.","PeriodicalId":147803,"journal":{"name":"Proceedings of the International Multiconference on Computer Science and Information Technology","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Coevolutionary algorithm for rule induction\",\"authors\":\"P. Myszkowski\",\"doi\":\"10.1109/IMCSIT.2010.5679728\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes our last research results in the field of evolutionary algorithms for rule extraction applied to classification (and image annotation). We focus on the data mining classification task and we propose evolutionary algorithm for rule extraction. Presented approach is based on binary classical genetic algorithm with representation of `if-then' rules and we propose two specialized genetic operators. We want to show that some search space reduction techniques make possible to get solution comparable to others from literature. To present our method ability of discovering the set of rules with high F-score we tested our approach on four benchmark datasets and ImageCLEF competition dataset.\",\"PeriodicalId\":147803,\"journal\":{\"name\":\"Proceedings of the International Multiconference on Computer Science and Information Technology\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Multiconference on Computer Science and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMCSIT.2010.5679728\",\"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 the International Multiconference on Computer Science and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMCSIT.2010.5679728","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper describes our last research results in the field of evolutionary algorithms for rule extraction applied to classification (and image annotation). We focus on the data mining classification task and we propose evolutionary algorithm for rule extraction. Presented approach is based on binary classical genetic algorithm with representation of `if-then' rules and we propose two specialized genetic operators. We want to show that some search space reduction techniques make possible to get solution comparable to others from literature. To present our method ability of discovering the set of rules with high F-score we tested our approach on four benchmark datasets and ImageCLEF competition dataset.