I. D. Falco, A. Iazzetta, E. Tarantino, Antonio Della Cioppa
{"title":"An evolutionary system for automatic explicit rule extraction","authors":"I. D. Falco, A. Iazzetta, E. Tarantino, Antonio Della Cioppa","doi":"10.1109/CEC.2000.870331","DOIUrl":null,"url":null,"abstract":"The search for novel and useful patterns within large databases, known as data mining, has become of great importance owing to the ever-increasing amounts of data collected by large organizations. In particular, the emphasis is on heuristic search methods which are able to discover patterns that are hard or impossible to detect using standard query mechanisms and classical statistical techniques. In this paper, an evolutionary system that is capable of extracting explicit classification rules is presented. The results are compared with those obtained by other approaches.","PeriodicalId":218136,"journal":{"name":"Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2000.870331","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
The search for novel and useful patterns within large databases, known as data mining, has become of great importance owing to the ever-increasing amounts of data collected by large organizations. In particular, the emphasis is on heuristic search methods which are able to discover patterns that are hard or impossible to detect using standard query mechanisms and classical statistical techniques. In this paper, an evolutionary system that is capable of extracting explicit classification rules is presented. The results are compared with those obtained by other approaches.