| Title: | OS12-1 A Rule-Based Classification System Enhanced by Multi-Objective Genetic Algorithm |
|---|---|
| Publication: | ICAROB2017 |
| Volume: | 22 |
| Pages: | 650-653 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2017.OS12-1 |
| Author(s): | Kenzoh Azakami, Shingo Mabu, Masanao Obayashi, Takashi Kuremoto |
| Publication Date: | January 19, 2017 |
| Keywords: | |
| Abstract: | Recent years, data mining techniques have been developed for extracting rules from big data. However, there are some problems to be considered, for example, it is difficult to judge which rules are important and which are not important; and even in simple classification problems with the small number of classes, a various sub-patterns to be considered potentially exist in each class. To solve the above problems, a rule clustering algorithm using multiobjective genetic algorithm is proposed. |
| PDF File: | https://alife-robotics.co.jp/members2017/icarob/data/html/data/OS_pdf/OS12/OS12-1.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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