Presentation | 1996/1/18 Decision Tree Learner Handling Tree-Structured Attributes Yasuhiro AKIBA, Hussein ALMUALLIM, Shigeo KANEDA, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper studies the problem of learning decision trees when the attributes of the domain are tree-structured. Quinlan suggests a pre-processing approach to this problem. When the size of the hierarchies used is huge, his approach is not efficient and effective. We introduce our own approach which handles tree-structured attributes directly without the need for pre-processing. We present experiments on natural and artificial data that suggest that our direct approach leads to better generalization performance than the Quinlan-encoding approach and runs roughly two to four times faster. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Machine Learning / Knowledge Acquisition / Natural Language Processing |
Paper # | AI95-45 |
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Conference Information | |
Committee | AI |
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Conference Date | 1996/1/18(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 | 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) | Decision Tree Learner Handling Tree-Structured Attributes |
Sub Title (in English) | |
Keyword(1) | Machine Learning |
Keyword(2) | Knowledge Acquisition |
Keyword(3) | Natural Language Processing |
1st Author's Name | Yasuhiro AKIBA |
1st Author's Affiliation | NTT Communication Science Labs() |
2nd Author's Name | Hussein ALMUALLIM |
2nd Author's Affiliation | King Fahd University of Petroleum and Minerals |
3rd Author's Name | Shigeo KANEDA |
3rd Author's Affiliation | NTT Communication Science Labs |
Date | 1996/1/18 |
Paper # | AI95-45 |
Volume (vol) | vol.95 |
Number (no) | 460 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |