{"title":"Heuristic Attempts to Improve the Generalization Capacities in Learning SVMs","authors":"L. State, C. Cocianu, Marinela Mircea","doi":"10.1109/SNPD.2012.37","DOIUrl":null,"url":null,"abstract":"The paper reports some new variants of gradient ascent type in learning SVMs. The theoretical development is presented in the third section of the paper. The performance analysis of the proposed variants, in terms of recognition accuracy and generalization capacity, is experimentally evaluated and the results are presented and commented in the final part of the paper.","PeriodicalId":387936,"journal":{"name":"2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2012.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The paper reports some new variants of gradient ascent type in learning SVMs. The theoretical development is presented in the third section of the paper. The performance analysis of the proposed variants, in terms of recognition accuracy and generalization capacity, is experimentally evaluated and the results are presented and commented in the final part of the paper.
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