{"title":"离散和连续变量的贝叶斯网络结构学习","authors":"J. Suzuki","doi":"10.1109/URKE.2012.6319529","DOIUrl":null,"url":null,"abstract":"We consider estimation of Bayesian network structures given a finite number of examples when both discrete and continuous random variables are present in a Bayesian network.","PeriodicalId":277189,"journal":{"name":"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering","volume":"2 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Bayesian network structure learning for discrete and continuous variables\",\"authors\":\"J. Suzuki\",\"doi\":\"10.1109/URKE.2012.6319529\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider estimation of Bayesian network structures given a finite number of examples when both discrete and continuous random variables are present in a Bayesian network.\",\"PeriodicalId\":277189,\"journal\":{\"name\":\"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering\",\"volume\":\"2 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/URKE.2012.6319529\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URKE.2012.6319529","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bayesian network structure learning for discrete and continuous variables
We consider estimation of Bayesian network structures given a finite number of examples when both discrete and continuous random variables are present in a Bayesian network.