Generating C4.5 Production Rules in Parallel

Abstract

Induction systems that represent concepts in the form of production rules have proven to be useful in a variety of domains where both accuracy and comprehensibility of the resulting models are important. However, the computational requirements for inducing a set of rules from large, noisy training sets can be enormous, so that techniques for improving the performance of rule induction systems by exploiting parallelism are of considerable interest. Recent work to parallelize the C4.5 rule generator algorithm is described. After presenting an overview of the algorithm and the parallelization strategy employed, empirical results of the parallel implementation that demonstrate substantial speedup over serial execution are provided. Introduction Algorithms for supervised learning have been widely studied in the artificial intelligence community over the past several decades. With the recent surge of interest in systems for knowledge discovery in databases (KDD), many of these algorithms ha...