{"title":"多类分类方法ECOC的计算复杂度研究","authors":"H. Danoyan","doi":"10.1109/CSITECHNOL.2017.8312149","DOIUrl":null,"url":null,"abstract":"The multiclass classification approach known as ECOC (error correcting output codes) is considered. The method solves the multiclass classification problem by combining binary classification algorithms according to some binary matrix. The framework is considered where the columns of the mentioned matrix are selected from the given set. It is proved that the algorithmic problem of column selection optimizing the training error is NP complete.","PeriodicalId":332371,"journal":{"name":"2017 Computer Science and Information Technologies (CSIT)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On computational complexity of multiclass classification approach ECOC\",\"authors\":\"H. Danoyan\",\"doi\":\"10.1109/CSITECHNOL.2017.8312149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The multiclass classification approach known as ECOC (error correcting output codes) is considered. The method solves the multiclass classification problem by combining binary classification algorithms according to some binary matrix. The framework is considered where the columns of the mentioned matrix are selected from the given set. It is proved that the algorithmic problem of column selection optimizing the training error is NP complete.\",\"PeriodicalId\":332371,\"journal\":{\"name\":\"2017 Computer Science and Information Technologies (CSIT)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Computer Science and Information Technologies (CSIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSITECHNOL.2017.8312149\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Computer Science and Information Technologies (CSIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSITECHNOL.2017.8312149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On computational complexity of multiclass classification approach ECOC
The multiclass classification approach known as ECOC (error correcting output codes) is considered. The method solves the multiclass classification problem by combining binary classification algorithms according to some binary matrix. The framework is considered where the columns of the mentioned matrix are selected from the given set. It is proved that the algorithmic problem of column selection optimizing the training error is NP complete.