{"title":"非对称核方法及其在fisher判别中的应用","authors":"Naoya Koide, Yukihiko Yamashita","doi":"10.1109/ICPR.2006.278","DOIUrl":null,"url":null,"abstract":"In this paper, we propose the asymmetric kernel method. Furthermore, we apply it to Fisher's discriminant and provide an kernel Fisher's discriminant with variable kernel parameters. We also provide the experimental result of the existing and the new kernel Fisher's discriminants by using several standard datasets and show the advantage of our method","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Asymmetric kernel method and its application to Fisher’s discriminant\",\"authors\":\"Naoya Koide, Yukihiko Yamashita\",\"doi\":\"10.1109/ICPR.2006.278\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose the asymmetric kernel method. Furthermore, we apply it to Fisher's discriminant and provide an kernel Fisher's discriminant with variable kernel parameters. We also provide the experimental result of the existing and the new kernel Fisher's discriminants by using several standard datasets and show the advantage of our method\",\"PeriodicalId\":236033,\"journal\":{\"name\":\"18th International Conference on Pattern Recognition (ICPR'06)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"18th International Conference on Pattern Recognition (ICPR'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2006.278\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th International Conference on Pattern Recognition (ICPR'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2006.278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Asymmetric kernel method and its application to Fishers discriminant
In this paper, we propose the asymmetric kernel method. Furthermore, we apply it to Fisher's discriminant and provide an kernel Fisher's discriminant with variable kernel parameters. We also provide the experimental result of the existing and the new kernel Fisher's discriminants by using several standard datasets and show the advantage of our method