Presentation | 1997/5/23 Regularizing the Cascade Correlation Algorithm to Avoid Weight-illgrowth Qun XU, Kenji NAKAYAMA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper investigates some possible problems of Cascade Correlation algorithm, one of which is the zigzag output mapping caused by weight-illgrowth of the adding hidden unit. Without doubt, it could lead to deteriorate the generialization, especially for regression problems. To solve this problem, we combine Cascade Correlation algorithm with regular-ization theory. In addition, some new regularization terms are proposed in light of special cascade structure. Simulation has shown that regularization indeedly smooth the zigzag output, so that the generialization is improved, especially for functional approximation. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | neural network / dynamic learning algorithm / cascade correlation / generialization / regularization |
Paper # | NC97-3 |
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Committee | NC |
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Conference Date | 1997/5/23(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Regularizing the Cascade Correlation Algorithm to Avoid Weight-illgrowth |
Sub Title (in English) | |
Keyword(1) | neural network |
Keyword(2) | dynamic learning algorithm |
Keyword(3) | cascade correlation |
Keyword(4) | generialization |
Keyword(5) | regularization |
1st Author's Name | Qun XU |
1st Author's Affiliation | Fac. Engineering, Kanazawa Univ.() |
2nd Author's Name | Kenji NAKAYAMA |
2nd Author's Affiliation | Fac. Engineering, Kanazawa Univ. |
Date | 1997/5/23 |
Paper # | NC97-3 |
Volume (vol) | vol.97 |
Number (no) | 69 |
Page | pp.pp.- |
#Pages | 8 |
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