| Presentation | 1998/9/17 Support Vector Machine and Kernel Based Nonlinear Subspace Method Eisaku MAEDA, Hiroshi MURASE, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Kernel Based Nonlinear Subspace Method(KNS method)is proposed for multi-class pattern classification.This method consists of the nonlinear transformation of original feature spaces defined by kernel functions and the linear subspace method in the transformed high-dimensional spaces. While the Support Vector Machine, a nonlinear classification method based on a kernel function technique, shows high classification performance, however, its computational cost exponentially increases according to the increase in the number of patterns and classes.The linear subspace method is a well-known technique for multi-class classification.It is not applicable, however, when the distribution of patterns has nonlinear characteristics or the dimension of feature space is low compared to the number of classes.The proposed method combimes the advantages of both techniques and could realize a multi-class nonlinear classifier with higher performance in less computational time.In this paper, we show the nonlinear subspace method can be formulated by nonlinear transformation defined by kernel functions and its classification performance is better than that obtained by conventional method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | pattern recognition / nonlinear subspace method / kernel function / dupport vector machine |
| Paper # | PRMU98-81 |
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| Committee | PRMU |
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| Conference Date | 1998/9/17(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Pattern Recognition and Media Understanding (PRMU) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Support Vector Machine and Kernel Based Nonlinear Subspace Method |
| Sub Title (in English) | |
| Keyword(1) | pattern recognition |
| Keyword(2) | nonlinear subspace method |
| Keyword(3) | kernel function |
| Keyword(4) | dupport vector machine |
| 1st Author's Name | Eisaku MAEDA |
| 1st Author's Affiliation | NTT Basic Research Laboratories() |
| 2nd Author's Name | Hiroshi MURASE |
| 2nd Author's Affiliation | NTT Basic Research Laboratories |
| Date | 1998/9/17 |
| Paper # | PRMU98-81 |
| Volume (vol) | vol.98 |
| Number (no) | 274 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |