{"title":"t型樱桃结树的若干改良","authors":"E. Kovács, T. Szántai","doi":"10.1109/CANS.2008.22","DOIUrl":null,"url":null,"abstract":"One of the important areas of machine learning is the development and use of probabilistic models for classification and prediction. In our earlier work we introduced a special kind of junction tree, based on a hypergraph structure called t-cherry tree and on some information theoretical concepts. In this paper we present a possibility for the improvement of these junction trees, by ldquocutting and refittingrdquo of the junction treepsilas branches. Both theoretical and experimental results demonstrate the improvement of the junction tree obtained after ldquobranch cutting and refittingrdquo.","PeriodicalId":50026,"journal":{"name":"Journal of Systems Science & Complexity","volume":"88 2 1","pages":"117-125"},"PeriodicalIF":2.6000,"publicationDate":"2008-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Some Improvements of t-Cherry Junction Trees\",\"authors\":\"E. Kovács, T. Szántai\",\"doi\":\"10.1109/CANS.2008.22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the important areas of machine learning is the development and use of probabilistic models for classification and prediction. In our earlier work we introduced a special kind of junction tree, based on a hypergraph structure called t-cherry tree and on some information theoretical concepts. In this paper we present a possibility for the improvement of these junction trees, by ldquocutting and refittingrdquo of the junction treepsilas branches. Both theoretical and experimental results demonstrate the improvement of the junction tree obtained after ldquobranch cutting and refittingrdquo.\",\"PeriodicalId\":50026,\"journal\":{\"name\":\"Journal of Systems Science & Complexity\",\"volume\":\"88 2 1\",\"pages\":\"117-125\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2008-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Systems Science & Complexity\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1109/CANS.2008.22\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Systems Science & Complexity","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1109/CANS.2008.22","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
One of the important areas of machine learning is the development and use of probabilistic models for classification and prediction. In our earlier work we introduced a special kind of junction tree, based on a hypergraph structure called t-cherry tree and on some information theoretical concepts. In this paper we present a possibility for the improvement of these junction trees, by ldquocutting and refittingrdquo of the junction treepsilas branches. Both theoretical and experimental results demonstrate the improvement of the junction tree obtained after ldquobranch cutting and refittingrdquo.
期刊介绍:
The Journal of Systems Science and Complexity is dedicated to publishing high quality papers on mathematical theories, methodologies, and applications of systems science and complexity science. It encourages fundamental research into complex systems and complexity and fosters cross-disciplinary approaches to elucidate the common mathematical methods that arise in natural, artificial, and social systems. Topics covered are:
complex systems,
systems control,
operations research for complex systems,
economic and financial systems analysis,
statistics and data science,
computer mathematics,
systems security, coding theory and crypto-systems,
other topics related to systems science.