Abstract
In this paper, a new clustering algorithm inspired by magnetic force is proposed. This algorithm is not sensitive to the initialization problem of cluster centroids. Centroid particles change their position according to the total magnetic force applied by data points. The position of the particle gets updated by employing magnetic resultant force to find the best position of centroid particle for clustering. To evaluate the performance of the proposed algorithm, numerical experiments are conducted on eleven benchmark data sets taken from UCI repository and are compared with five different clustering algorithms. The results show that the proposed algorithms are more accurate, efficient and robust as compared to the other clustering algorithms.
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