| Presentation | 1996/3/18 On the statistical properties of regression model using step-type basis functions Taichi HAYASAKA, katsuyuki HAGIWARA, Naohiro TODA, Shiro USUI, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | One of the differences between the regression models using the function representations of 3-layered neural networks and the traditional linear regression models is whether the nonlinear parameters associated with the basis functions exist or not, where these parameters play a role of varying the form of the basis so as to minimize the square error. In this study, we gave attention to this feature and defined the regression model using a function representation with strep-type discrete variable basis. Then we obtained the bounds of the asymptotic expectations of the least square error and the prediction square error with respect to the sample distribution using the extreme value theory. These results will provide an effective approach to the statistical properties of 3-layered neural networks. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | function representation with discrete variable basis / step-type basis function / regression model / square error / extreme value theory |
| Paper # | NC-95-128 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1996/3/18(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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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) | On the statistical properties of regression model using step-type basis functions |
| Sub Title (in English) | |
| Keyword(1) | function representation with discrete variable basis |
| Keyword(2) | step-type basis function |
| Keyword(3) | regression model |
| Keyword(4) | square error |
| Keyword(5) | extreme value theory |
| 1st Author's Name | Taichi HAYASAKA |
| 1st Author's Affiliation | Department of Information and Computer Sciences, Toyohashi University of Technology() |
| 2nd Author's Name | katsuyuki HAGIWARA |
| 2nd Author's Affiliation | Faculty of Electrical and Electronic Engineering, Mie University |
| 3rd Author's Name | Naohiro TODA |
| 3rd Author's Affiliation | Department of Information and Computer Sciences, Toyohashi University of Technology |
| 4th Author's Name | Shiro USUI |
| 4th Author's Affiliation | Department of Information and Computer Sciences, Toyohashi University of Technology |
| Date | 1996/3/18 |
| Paper # | NC-95-128 |
| Volume (vol) | vol.95 |
| Number (no) | 598 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |