Presentation | 2000/7/12 Acquiring a Single Decision Tree Representation of Majority Voting Classifiers Yasuhiro AKIBA, Shigeo KANEDA, Hussein ALMUALLIM, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper addresses two problems in Majority voting classifiers(MVCs)like Bagging:(1)no logical reasoning behind the decision and(2)a large amount of classification time and space for significant accuracy boosting.To solve these problems, this paper proposes a method for learning a single decision tree that approximates MVCs.The method learns a DT from the original examples and the meta examples that are generated from each classifier joining MVCs.Experimental results show that the method has similar accuracy to Bagging and that the tree size by the method is as large as the size of two classifiers. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Machine Learning / Decision Tree / Majority Voting / Accuracy Boosting / Averaging |
Paper # | OFS2000-26,AI2000-28 |
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Committee | AI |
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Conference Date | 2000/7/12(1days) |
Place (in Japanese) | (See Japanese page) |
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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) | Acquiring a Single Decision Tree Representation of Majority Voting Classifiers |
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Keyword(1) | Machine Learning |
Keyword(2) | Decision Tree |
Keyword(3) | Majority Voting |
Keyword(4) | Accuracy Boosting |
Keyword(5) | Averaging |
1st Author's Name | Yasuhiro AKIBA |
1st Author's Affiliation | NTT Communication Science Labs.() |
2nd Author's Name | Shigeo KANEDA |
2nd Author's Affiliation | Doshisha Univ. |
3rd Author's Name | Hussein ALMUALLIM |
3rd Author's Affiliation | King Fahd Univ.of Petroleum & Minerals |
Date | 2000/7/12 |
Paper # | OFS2000-26,AI2000-28 |
Volume (vol) | vol.100 |
Number (no) | 199 |
Page | pp.pp.- |
#Pages | 8 |
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