| Presentation | 2002/3/15 Ordering Hypotheses by Prioritized Inductive Learning Kousuke TSUJITA, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Induction is a learning method for drawing a general rule from the background knowledge and observed examples. Existing induction systems do not consider priority relations between acquired knowledge. However, in the real world a person puts priorities over his knowledge and appropriately uses it. In this research, we propose a method for ordering inductive hypotheses based on observations. When a new observation is given to the background knowledge base, the explanation structure of the observation is produced and hypotheses are quantitatively ordered using Bayes theorem. As a result, the system can dynamically change the ranking of hypotheses according to the rate of the instances/exceptions of a concept in observations. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Machine Learning / Inductive Learning / Probabilistic Reasoning / Knowledge Information Processing / Bayesian Network |
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| Conference Information | |
| Committee | AI |
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| Conference Date | 2002/3/15(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Ordering Hypotheses by Prioritized Inductive Learning |
| Sub Title (in English) | |
| Keyword(1) | Machine Learning |
| Keyword(2) | Inductive Learning |
| Keyword(3) | Probabilistic Reasoning |
| Keyword(4) | Knowledge Information Processing |
| Keyword(5) | Bayesian Network |
| 1st Author's Name | Kousuke TSUJITA |
| 1st Author's Affiliation | Faculty of Systems Engineering Wakayama University() |
| Date | 2002/3/15 |
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| Volume (vol) | vol.101 |
| Number (no) | 742 |
| Page | pp.pp.- |
| #Pages | 8 |
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