{"title":"基于偏二叉树算法的最小二乘双支持向量机","authors":"Qing Yu, R. Liu","doi":"10.1109/CISP-BMEI.2018.8633117","DOIUrl":null,"url":null,"abstract":"Based on the classic least squares twin support vector machine (LSTSVM), an efficient but simple Least Squares Twin Support Vector Machine-Partial Binary Tree (LSTSVM-PBT)for binary classification problem was proposed. This algorithm introduces binary tree into LSTSVM, the problem summed up as binary tree classification for each data ultimately. Compared to traditional SVM, LSTSVM-PBT has low time complexity. Reliable theoretical analysis and extensive experiments show that LSTBSVM-PBT is fast computationally and obtain the higher performance than traditional algorithm.","PeriodicalId":117227,"journal":{"name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Least Squares Twin SVM Based on Partial Binary Tree Algorithm\",\"authors\":\"Qing Yu, R. Liu\",\"doi\":\"10.1109/CISP-BMEI.2018.8633117\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the classic least squares twin support vector machine (LSTSVM), an efficient but simple Least Squares Twin Support Vector Machine-Partial Binary Tree (LSTSVM-PBT)for binary classification problem was proposed. This algorithm introduces binary tree into LSTSVM, the problem summed up as binary tree classification for each data ultimately. Compared to traditional SVM, LSTSVM-PBT has low time complexity. Reliable theoretical analysis and extensive experiments show that LSTBSVM-PBT is fast computationally and obtain the higher performance than traditional algorithm.\",\"PeriodicalId\":117227,\"journal\":{\"name\":\"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP-BMEI.2018.8633117\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI.2018.8633117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Least Squares Twin SVM Based on Partial Binary Tree Algorithm
Based on the classic least squares twin support vector machine (LSTSVM), an efficient but simple Least Squares Twin Support Vector Machine-Partial Binary Tree (LSTSVM-PBT)for binary classification problem was proposed. This algorithm introduces binary tree into LSTSVM, the problem summed up as binary tree classification for each data ultimately. Compared to traditional SVM, LSTSVM-PBT has low time complexity. Reliable theoretical analysis and extensive experiments show that LSTBSVM-PBT is fast computationally and obtain the higher performance than traditional algorithm.