| Presentation | 2005/3/23 Online Variable Selection From Multi-Dimentional Successively Data Ryuji OSHIMA, Koichiro YAMAUCHI, Takashi OMORI, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Variable selection from multi-dimensional inputs is very important issue for effective machine learning. Although, many any researchers have proposed various types of techniques to achieve the variable selection, almost all of them are based on off-line learning manner. In this paper, we propose a new paradigm to achieve quick variable selection. The new method generates various candidates selecting various variable subset which is likely to be useful. Then, the candidates are evaluated simultaneously, and the important variables are determined according to prediction accuracy. In the computer simulation, we show that the system realizes reasonable online variable selection. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | real time / variable selection / Online learning / Nearest Neighbor |
| Paper # | NC2004-223 |
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| Committee | NC |
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| Conference Date | 2005/3/23(1days) |
| Place (in Japanese) | (See Japanese page) |
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| 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) | Online Variable Selection From Multi-Dimentional Successively Data |
| Sub Title (in English) | |
| Keyword(1) | real time |
| Keyword(2) | variable selection |
| Keyword(3) | Online learning |
| Keyword(4) | Nearest Neighbor |
| 1st Author's Name | Ryuji OSHIMA |
| 1st Author's Affiliation | Graduate School of Information Science and Technology, Hokkaido University() |
| 2nd Author's Name | Koichiro YAMAUCHI |
| 2nd Author's Affiliation | Graduate School of Information Science and Technology, Hokkaido University |
| 3rd Author's Name | Takashi OMORI |
| 3rd Author's Affiliation | Graduate School of Information Science and Technology, Hokkaido University |
| Date | 2005/3/23 |
| Paper # | NC2004-223 |
| Volume (vol) | vol.104 |
| Number (no) | 760 |
| Page | pp.pp.- |
| #Pages | 5 |
| Date of Issue | |