An Effective Clustering Method Using a Discrete Particle Swarm Optimization Algorithm-Based Hybrid Approach

The purpose of this paper is to present and evaluate an improved Naive Bayes algorithm for clustering. Many researchers search for parameter values using EM algorithm. It is well-known that EM approach has a drawback - local optimal solution, so we propose a novel hybrid algorithm of the discrete particle swarm optimization (DPSO) and the EM approach to improve the global search performance. We evaluate this hybrid approach on 4 real-world data sets from UCI repository. In a number of experiments and comparisons, the hybrid DPSO+EM algorithm exhibits a more effective and outperforms the EM approach