Authors
Shingo Mabu, Kenzoh Azakami, Masanao Obayashi, Takashi Kuremoto
Corresponding Author
Shingo Mabu
Available Online 1 December 2017.
DOI
https://doi.org/10.2991/jrnal.2017.4.3.13
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 ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).