Title :
An m-of-n rule induction algorithm and its application to DNA domain
Author_Institution :
Dept. of Comput. Sci., Sydney Univ., NSW, Australia
Abstract :
An m-of-n concept is a restricted form of the disjunctive normal form. The purpose of this paper is firstly to introduce a learning algorithm that induces m-of-n rules, and secondly to present the performance of this algorithm when applied to the DNA domain. This paper explores a search method for m-of-n concepts that gives rise to a rule induction algorithm called MoN. A pruning strategy akin to alpha-beta pruning is employed to reduce the search space encountered in the exhaustive search. A set of rules that consists of a disjunction of m-of-n concepts is used in MoN, as opposed to the disjunction of conjunctive rules normally used in rule induction algorithms. We show the application of this algorithm in inducing rules for primate splice-junction gene sequences (DNA) and compare the results obtained from C4.5 rules and ID2-of-3 concepts.<>
Keywords :
DNA; biology computing; inference mechanisms; learning (artificial intelligence); search problems; C4.5 rules; DNA domain; ID2-of-3 concepts; MoN algorithm; alpha-beta pruning; disjunctive normal form; exhaustive search method; learning algorithm; m-of-n rule induction algorithm; performance; primate splice-junction gene sequences; pruning strategy; search space reduction;
Conference_Titel :
System Sciences, 1994. Proceedings of the Twenty-Seventh Hawaii International Conference on
Conference_Location :
Wailea, HI, USA
Print_ISBN :
0-8186-5090-7
DOI :
10.1109/HICSS.1994.323558
