| 书目名称 | Support Vector Machines for Pattern Classification |
| 编辑 | Shigeo Abe |
| 视频video | http://file.papertrans.cn/883/882147/882147.mp4 |
| 丛书名称 | Advances in Computer Vision and Pattern Recognition |
| 图书封面 |  |
| 描述 | I was shocked to see a student’s report on performance comparisons between support vector machines (SVMs) and fuzzy classi?ers that we had developed withourbestendeavors.Classi?cationperformanceofourfuzzyclassi?erswas comparable, but in most cases inferior, to that of support vector machines. This tendency was especially evident when the numbers of class data were small. I shifted my research e?orts from developing fuzzy classi?ers with high generalization ability to developing support vector machine–based classi?ers. This book focuses on the application of support vector machines to p- tern classi?cation. Speci?cally, we discuss the properties of support vector machines that are useful for pattern classi?cation applications, several m- ticlass models, and variants of support vector machines. To clarify their - plicability to real-world problems, we compare performance of most models discussed in the book using real-world benchmark data. Readers interested in the theoretical aspect of support vector machines should refer to books such as [109, 215, 256, 257]. |
| 出版日期 | Book 20051st edition |
| 关键词 | Fuzzy Systems; Kernel Methods; Pattern Classification; Support Vector Machines; classification; fuzzy; fuz |
| 版次 | 1 |
| doi | https://doi.org/10.1007/1-84628-219-5 |
| isbn_ebook | 978-1-84628-219-5Series ISSN 2191-6586 Series E-ISSN 2191-6594 |
| issn_series | 2191-6586 |
| copyright | Springer-Verlag London 2005 |
|Archiver|手机版|小黑屋|
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