| Presentation | 2006-01-24 Adaptive Classifiers-Ensemble System for Concept-Drifting Environments Kyosuke NISHIDA, Koichiro YAMAUCHI, Takashi OMORI, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Most machine learning algorithms assume stationary environments, require a large number of training examples in advance, and begin the learning from scratch. In contrast, humans learn in changing environments with sequential training examples and leverage past experiences as prior knowledge in new situations. To deal with real-world problems in changing environments, the ability to make human-like quick responses must be developed in machines. Many researchers have presented learning systems that assume the presence of hidden context and concept drift. In particular, several systems have been proposed that use ensembles of classifiers. These systems are generally robust against noise, but have problems leveraging prior knowledge of recurring contexts. Also, most of the systems cannot handle all property of the concept drifts. We proposed an online learning system that uses an ensemble of classifiers suitable for recent training examples and used experiments to show that this system can leverage prior knowledge of recurring contexts and respond to sudden changes. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | concept drift / drift detection / hidden context / multiple classifier systems / classifier ensembles |
| Paper # | NC2005-98 |
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| Committee | NC |
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| Conference Date | 2006/1/17(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) | Adaptive Classifiers-Ensemble System for Concept-Drifting Environments |
| Sub Title (in English) | |
| Keyword(1) | concept drift |
| Keyword(2) | drift detection |
| Keyword(3) | hidden context |
| Keyword(4) | multiple classifier systems |
| Keyword(5) | classifier ensembles |
| 1st Author's Name | Kyosuke NISHIDA |
| 1st Author's Affiliation | Division of Synergetic Information Science, Graduate School of Information Science and Technology, Hokkaido University() |
| 2nd Author's Name | Koichiro YAMAUCHI |
| 2nd Author's Affiliation | Division of Synergetic Information Science, Graduate School of Information Science and Technology, Hokkaido University |
| 3rd Author's Name | Takashi OMORI |
| 3rd Author's Affiliation | Division of Synergetic Information Science, Graduate School of Information Science and Technology, Hokkaido University |
| Date | 2006-01-24 |
| Paper # | NC2005-98 |
| Volume (vol) | vol.105 |
| Number (no) | 544 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |