{"title":"模糊决策森林","authors":"C. Janikow","doi":"10.1109/NAFIPS.2003.1226832","DOIUrl":null,"url":null,"abstract":"In the past, we have developed and presented a Fuzzy Decision Tree, more recently followed by an extension called a Fuzzy Decision Forest. The idea behind the forest is not only to represent multiple trees, but also to represent test alternatives at all levels of every tree. The resulting tree is in fact a 3-dimensional tree. A two-dimensional slice is equivalent to a single decision tree. The forest allows multiple choices of tests in some or all nodes of the decision tree. These alternative tests can be used to enhance the classification accuracy of the tree. However, the major advantage of having multiple test choices is to have alternative test decisions when features in test data are unreliable or just missing. In the paper, we overview the ideas behind Fuzzy Decision Forest, and we illustrate its enhanced capabilities with a number of experiments with missing features.","PeriodicalId":153530,"journal":{"name":"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fuzzy Decision Forest\",\"authors\":\"C. Janikow\",\"doi\":\"10.1109/NAFIPS.2003.1226832\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the past, we have developed and presented a Fuzzy Decision Tree, more recently followed by an extension called a Fuzzy Decision Forest. The idea behind the forest is not only to represent multiple trees, but also to represent test alternatives at all levels of every tree. The resulting tree is in fact a 3-dimensional tree. A two-dimensional slice is equivalent to a single decision tree. The forest allows multiple choices of tests in some or all nodes of the decision tree. These alternative tests can be used to enhance the classification accuracy of the tree. However, the major advantage of having multiple test choices is to have alternative test decisions when features in test data are unreliable or just missing. In the paper, we overview the ideas behind Fuzzy Decision Forest, and we illustrate its enhanced capabilities with a number of experiments with missing features.\",\"PeriodicalId\":153530,\"journal\":{\"name\":\"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2003.1226832\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2003.1226832","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In the past, we have developed and presented a Fuzzy Decision Tree, more recently followed by an extension called a Fuzzy Decision Forest. The idea behind the forest is not only to represent multiple trees, but also to represent test alternatives at all levels of every tree. The resulting tree is in fact a 3-dimensional tree. A two-dimensional slice is equivalent to a single decision tree. The forest allows multiple choices of tests in some or all nodes of the decision tree. These alternative tests can be used to enhance the classification accuracy of the tree. However, the major advantage of having multiple test choices is to have alternative test decisions when features in test data are unreliable or just missing. In the paper, we overview the ideas behind Fuzzy Decision Forest, and we illustrate its enhanced capabilities with a number of experiments with missing features.