Knowledge Discovery of Interesting Classification Rules Based on Adaptive Genetic Algorithm

DOI

10.2991/iske.2007.164How to use a DOI?

Keywords

data mining, genetic algorithm, classification rules, interesting rules

Abstract

Data classification is a very important point in Data Mining,but the existing classification algorithms always only discover the classification rules with high accuracy,and the research about interesting classification rules is few. So this paper proposed an algorithm to find the interesting classification rules based on Genetic Algorithm. Firstly, we design the fitness function with the attributes’ information gain, and the settings of the weight of the information gain, and the interestingness of the rules, so we combine the objective and subjective measure methods together. Secondly, we use the adaptive Genetic Algorithm to keep the process from constringency early, then, we can reduce the convergence speed. At last, the results of the experiment given by JBuilder2006 could discover the interesting classification rules, illustrating the effectiveness of this algorithm.

Copyright

© 2007, 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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TY  - CONF
AU  - Yong Zhou
PY  - 2007/10
DA  - 2007/10
TI  - Knowledge Discovery of Interesting Classification Rules Based on Adaptive Genetic Algorithm
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 964
EP  - 970
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.164
DO  - 10.2991/iske.2007.164
ID  - Zhou2007/10
ER  -