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Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/15371
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| Title: | A new algorithm for automatic knowledge acquisition in inductive learning |
| Authors: | Ömer Akgöbek
Yavuz Selim Aydin
Ercan Öztemel
Mehmet Sabih Aksoy |
| Keywords: | Knowledge acquisition; Inductive learning; Rule extraction; Entropy; Machine learning |
| Issue Date: | 2005 |
| Publisher: | Elsevier |
| Abstract: | The objective of this study is to present a new algorithm, REX-1, developed for automatic knowledge acquisition in Inductive Learning. It aims at eliminating the pitfalls and disadvantages of the techniques and algorithms currently in use. The proposed algorithm makes use of the direct rule extraction approach, rather than the decision tree. For this purpose, it uses a set of examples to induce general rules. Using some widely used set of examples such as IRIS, Balance and Balloons, Monk, Splice, Promoter, Lenses, Zoo, and Vote, our algorithm is compared with other well-known algorithms such as ID3, C4.5, ILA, and Rules Family. |
| URI: | http://hdl.handle.net/123456789/15371 |
| Appears in Collections: | College of Computer and Information Sciences
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