Presentation | 2014/2/6 Improved Subspace-based Support Vector Machines by linear combination of the separating hyper-planes Shota FUNAKI, Takuya KITAMURA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this paper, we propose the improved subspace-based SVMs (SS-SVMs) by linearly-combining the separating hyper-planes (LCS-SVMs). In this method, the discriminant function, which is determined in the training of the conventional SS-SVMs, for each class is denned as a feature quantity. With these feature quantities, the new discriminant functions are optimized by SVMs. Thus, for each class, LCS-SVMs can generate the separating hyper-planes including the information of other class feature spaces. In addition, the learning cost of LCS-SVM will be about as low as SS-SVM if the number of class is not too big. Using benchmark set, we evaluate the effectiveness of the proposed method. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Support vector machine / Multi-class classifier / Pattern recognition / Subspace method |
Paper # | CNR2013-43,PRMU2013-135 |
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Conference Information | |
Committee | CNR |
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Conference Date | 2014/2/6(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Cloud Network Robotics (CNR) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Improved Subspace-based Support Vector Machines by linear combination of the separating hyper-planes |
Sub Title (in English) | |
Keyword(1) | Support vector machine |
Keyword(2) | Multi-class classifier |
Keyword(3) | Pattern recognition |
Keyword(4) | Subspace method |
1st Author's Name | Shota FUNAKI |
1st Author's Affiliation | Department of Electrical Engineering, Toyama National College of Technology() |
2nd Author's Name | Takuya KITAMURA |
2nd Author's Affiliation | Department of Electrical Engineering, Toyama National College of Technology |
Date | 2014/2/6 |
Paper # | CNR2013-43,PRMU2013-135 |
Volume (vol) | vol.113 |
Number (no) | 432 |
Page | pp.pp.- |
#Pages | 6 |
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