Basheer M. Al-Maqaleh and Kamal K. Bharadwaj
Genetic Programming Approach to Hierarchical Production Rule Discovery
3534 - 3537
2007
1
11
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/10022
https://publications.waset.org/vol/11
World Academy of Science, Engineering and Technology
Automated discovery of hierarchical structures in
large data sets has been an active research area in the recent past.
This paper focuses on the issue of mining generalized rules with crisp
hierarchical structure using Genetic Programming (GP) approach to
knowledge discovery. The postprocessing scheme presented in this
work uses flat rules as initial individuals of GP and discovers
hierarchical structure. Suitable genetic operators are proposed for the
suggested encoding. Based on the Subsumption Matrix(SM), an
appropriate fitness function is suggested. Finally, Hierarchical
Production Rules (HPRs) are generated from the discovered
hierarchy. Experimental results are presented to demonstrate the
performance of the proposed algorithm.
Open Science Index 11, 2007