Presentation | 2003/7/22 Analysis of ensemble learning using simple perceptrons based on on-line learning theory Seiji MIYOSHI, Kazuyuki HARA, Masato OKADA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We discuss the ensemble learning using K nonlinear simple perceptrons of which an output function is the sign function based on the on-line learning in the finite K case. First, we derive a macroscopic differential equation describing a dynamics of correlation q between the student weight vectors in a general learning algorithm. Second, we apply the equation to the three well-known rules, that is the Hebb rule, the Perceptron rule and the AdaTron rule, and solve those numerically. Third, we obtain the generalization error of these ensemble machines using a majority vote of students. As result, we show that the correlation between the student weight vectors in the AdaTron rule evolves most slowly, and that the AdaTron rule is the most superior among the three learning rules in the framework of the ensemble learning. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | ensemble learning / on-line learning / nonlinear perceptron / Perceptron rule / Hebb rule / AdaTron rule / generalization error |
Paper # | NC2003-36 |
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Committee | NC |
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Conference Date | 2003/7/22(1days) |
Place (in Japanese) | (See Japanese page) |
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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) | Analysis of ensemble learning using simple perceptrons based on on-line learning theory |
Sub Title (in English) | |
Keyword(1) | ensemble learning |
Keyword(2) | on-line learning |
Keyword(3) | nonlinear perceptron |
Keyword(4) | Perceptron rule |
Keyword(5) | Hebb rule |
Keyword(6) | AdaTron rule |
Keyword(7) | generalization error |
1st Author's Name | Seiji MIYOSHI |
1st Author's Affiliation | Kobe City College of Technology() |
2nd Author's Name | Kazuyuki HARA |
2nd Author's Affiliation | Tokyo Metropolitan College of Technology |
3rd Author's Name | Masato OKADA |
3rd Author's Affiliation | RIKEN Brain Science Institute:JST PRESTO |
Date | 2003/7/22 |
Paper # | NC2003-36 |
Volume (vol) | vol.103 |
Number (no) | 228 |
Page | pp.pp.- |
#Pages | 6 |
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