| Presentation | 2000/2/3 Bias Estimation and Model Selection Masashi Sugiyama, Hidemitsu Ogawa, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The problem of model selection is considerably important for acquiring higher levels of generalization capability in supervised learning. So far, Akaike information criterion (AIC) is widely used for model selection. However, AIC does not work well when the number of training examples is small because of the asymptotic approximation. In this paper, we propose a new criterion for model selection called the subspace information criterion (SIC). Computer simulations show that SIC works well even when the number of training examples is small. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Supervised learning, Generalization capability / Model selection / Information criterion / Akaike's information criterion(AIC) / Bias/Variance |
| Paper # | NC99-81 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 2000/2/3(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Bias Estimation and Model Selection |
| Sub Title (in English) | |
| Keyword(1) | Supervised learning, Generalization capability |
| Keyword(2) | Model selection |
| Keyword(3) | Information criterion |
| Keyword(4) | Akaike's information criterion(AIC) |
| Keyword(5) | Bias/Variance |
| 1st Author's Name | Masashi Sugiyama |
| 1st Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology() |
| 2nd Author's Name | Hidemitsu Ogawa |
| 2nd Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology |
| Date | 2000/2/3 |
| Paper # | NC99-81 |
| Volume (vol) | vol.99 |
| Number (no) | 612 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |