{"title":"一种鲁棒q型主成分分析的快速算法","authors":"J. Almhana, V. Choulakian","doi":"10.1109/HPCSA.2002.1019145","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new method for the computation of the algorithm of robust Q-mode principal component analysis (RQMPCA) used in statistics. We will show how we can reduce the computation complexity of this algorithm by p, where p is the number of variables. An application, on web document retrieval time, was studied using this algorithm. We will report some statistical results on retrieval time and its relationship with document's size and its number of objects.","PeriodicalId":111862,"journal":{"name":"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A fast algorithm for the computation of robust Q-mode principal component analysis in L\",\"authors\":\"J. Almhana, V. Choulakian\",\"doi\":\"10.1109/HPCSA.2002.1019145\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new method for the computation of the algorithm of robust Q-mode principal component analysis (RQMPCA) used in statistics. We will show how we can reduce the computation complexity of this algorithm by p, where p is the number of variables. An application, on web document retrieval time, was studied using this algorithm. We will report some statistical results on retrieval time and its relationship with document's size and its number of objects.\",\"PeriodicalId\":111862,\"journal\":{\"name\":\"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCSA.2002.1019145\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCSA.2002.1019145","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fast algorithm for the computation of robust Q-mode principal component analysis in L
In this paper, we propose a new method for the computation of the algorithm of robust Q-mode principal component analysis (RQMPCA) used in statistics. We will show how we can reduce the computation complexity of this algorithm by p, where p is the number of variables. An application, on web document retrieval time, was studied using this algorithm. We will report some statistical results on retrieval time and its relationship with document's size and its number of objects.