Volume 4, Issue 3, December 2017, Pages 239 - 242
A Rule-Based Classification System Enhanced by Multi-Objective Genetic Algorithm
Authors
Shingo Mabu, Kenzoh Azakami, Masanao Obayashi, Takashi Kuremoto
Corresponding Author
Shingo Mabu
Available Online 1 December 2017.
- DOI
- 10.2991/jrnal.2017.4.3.13How to use a DOI?
- 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 multi-objective genetic algorithm is proposed.
- Copyright
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Shingo Mabu AU - Kenzoh Azakami AU - Masanao Obayashi AU - Takashi Kuremoto PY - 2017 DA - 2017/12/01 TI - A Rule-Based Classification System Enhanced by Multi-Objective Genetic Algorithm JO - Journal of Robotics, Networking and Artificial Life SP - 239 EP - 242 VL - 4 IS - 3 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.2017.4.3.13 DO - 10.2991/jrnal.2017.4.3.13 ID - Mabu2017 ER -