Journal of Robotics, Networking and Artificial Life

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/).

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
4 - 3
Pages
239 - 242
Publication Date
2017/12/01
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
10.2991/jrnal.2017.4.3.13How to use a DOI?
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  -