{"title":"具有模糊数值属性的双分支决策树的归纳","authors":"D. Huang, Xizhao Wang, M. Ha","doi":"10.1109/ICMLC.2002.1167495","DOIUrl":null,"url":null,"abstract":"This paper presents an algorithm regarding the fuzzy number-valued attribute using the information entropy minimization heuristic. The algorithm gives us a desirable behavior of the information entropy of partitioning. The efficiency of the learning algorithm is improved by analyzing the non-stable cut point and the experiment result shows that the number of leaves in decision tree generation is reduced with the raising of level /spl alpha/. Thus, the scale of decision tree and the recognition rate of classification using the proposed algorithm are improved with the raising of level /spl alpha/. To the unknown-classified sample data, the algorithm offers a rapid matching speed. Finally, the example on medical records that we collected in a hospital shows the utility of the proposed algorithm.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"107 1","pages":"1662-1666 vol.3"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Induction of bi-branches decision tree with fuzzy number-value attribute\",\"authors\":\"D. Huang, Xizhao Wang, M. Ha\",\"doi\":\"10.1109/ICMLC.2002.1167495\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an algorithm regarding the fuzzy number-valued attribute using the information entropy minimization heuristic. The algorithm gives us a desirable behavior of the information entropy of partitioning. The efficiency of the learning algorithm is improved by analyzing the non-stable cut point and the experiment result shows that the number of leaves in decision tree generation is reduced with the raising of level /spl alpha/. Thus, the scale of decision tree and the recognition rate of classification using the proposed algorithm are improved with the raising of level /spl alpha/. To the unknown-classified sample data, the algorithm offers a rapid matching speed. Finally, the example on medical records that we collected in a hospital shows the utility of the proposed algorithm.\",\"PeriodicalId\":90702,\"journal\":{\"name\":\"Proceedings. International Conference on Machine Learning and Cybernetics\",\"volume\":\"107 1\",\"pages\":\"1662-1666 vol.3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2002.1167495\",\"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. International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2002.1167495","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Induction of bi-branches decision tree with fuzzy number-value attribute
This paper presents an algorithm regarding the fuzzy number-valued attribute using the information entropy minimization heuristic. The algorithm gives us a desirable behavior of the information entropy of partitioning. The efficiency of the learning algorithm is improved by analyzing the non-stable cut point and the experiment result shows that the number of leaves in decision tree generation is reduced with the raising of level /spl alpha/. Thus, the scale of decision tree and the recognition rate of classification using the proposed algorithm are improved with the raising of level /spl alpha/. To the unknown-classified sample data, the algorithm offers a rapid matching speed. Finally, the example on medical records that we collected in a hospital shows the utility of the proposed algorithm.