A new K-harmonic means based simplified swarm optimization for data mining

In this paper, we have developed an efficient hybrid data mining approach. The proposed data mining approach called gSSO is a modification introduced to simplified swarm optimization and based on K-harmonic means (KHM) algorithm to help the KHM algorithm escape from local optimum. To test its solution quality, the proposed gSSO is compared with other recently introduced KHM-based Algorithms in iris dataset in the UCI database. The experimental results conclude that the proposed gSSO outperforms other algorithms in the solution quality of all aspects (AVG, MIN, MAX, and STDEV) in space and stability.