| Presentation | 1997/3/17 Rule Extraction from Data with Continuous Valued Inputs and Discrete Valued Outputs using Neural Networks Hiroki Ueda, Masumi Ishikawa, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The paper focuses on rule extraction from data with continuous valued inputs and discrete valued-outputs. Considering the understandability of resulting rules, it is assumed that simple rules with large generalization ability are desirable. In order to obtain them, an information criterion representing this trade-off is used for model selection from among a set of networks with various complexities. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | rule extraction / structural learning / information criterion / continuous valued inputs |
| Paper # | NC96-121 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1997/3/17(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) | Rule Extraction from Data with Continuous Valued Inputs and Discrete Valued Outputs using Neural Networks |
| Sub Title (in English) | |
| Keyword(1) | rule extraction |
| Keyword(2) | structural learning |
| Keyword(3) | information criterion |
| Keyword(4) | continuous valued inputs |
| 1st Author's Name | Hiroki Ueda |
| 1st Author's Affiliation | Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology() |
| 2nd Author's Name | Masumi Ishikawa |
| 2nd Author's Affiliation | Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology |
| Date | 1997/3/17 |
| Paper # | NC96-121 |
| Volume (vol) | vol.96 |
| Number (no) | 583 |
| Page | pp.pp.- |
| #Pages | 8 |
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