{"title":"基于势的二值分类","authors":"E. Boczko, Andrew DiLullo, Todd R. Young","doi":"10.1109/OCCBIO.2009.31","DOIUrl":null,"url":null,"abstract":"We introduce a simple and computationally trivial method for binary classification based on the evaluation of potential functions. We demonstrate that despite the conceptual and computational simplicity of the method its performance can match or exceed that of standard SupportVector Machine methods.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Binary Classification Based on Potentials\",\"authors\":\"E. Boczko, Andrew DiLullo, Todd R. Young\",\"doi\":\"10.1109/OCCBIO.2009.31\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce a simple and computationally trivial method for binary classification based on the evaluation of potential functions. We demonstrate that despite the conceptual and computational simplicity of the method its performance can match or exceed that of standard SupportVector Machine methods.\",\"PeriodicalId\":231499,\"journal\":{\"name\":\"2009 Ohio Collaborative Conference on Bioinformatics\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Ohio Collaborative Conference on Bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OCCBIO.2009.31\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Ohio Collaborative Conference on Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCCBIO.2009.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We introduce a simple and computationally trivial method for binary classification based on the evaluation of potential functions. We demonstrate that despite the conceptual and computational simplicity of the method its performance can match or exceed that of standard SupportVector Machine methods.