{"title":"Analysis of the MSVMO method - the probabilistic SVM outputs","authors":"A. Madevska-Bogdanova, Z. Popeska, D. Nikolik","doi":"10.1109/ITI.2005.1491157","DOIUrl":null,"url":null,"abstract":"Number of experiments has shown that for classification problems, if SVM models trained over the same data set have similar SVM outputs with respect to a given input vector x, the values of the corresponding MSVMO probabilities [3] have small differences. This means that the information from the MSVMO method from different SVM models trained over the same data set is essentially the same.","PeriodicalId":392003,"journal":{"name":"27th International Conference on Information Technology Interfaces, 2005.","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"27th International Conference on Information Technology Interfaces, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITI.2005.1491157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Number of experiments has shown that for classification problems, if SVM models trained over the same data set have similar SVM outputs with respect to a given input vector x, the values of the corresponding MSVMO probabilities [3] have small differences. This means that the information from the MSVMO method from different SVM models trained over the same data set is essentially the same.