An efficient approximation to the K-means clustering for massive data

Marco Capó, Aritz Pérez, José Antonio Lozano

Abstract: Highlights•An approximation to the Kmeans algorithm for massive data problems is proposed.•RPKM reduces several orders of computations while obtaining good approximations.•RPKM reduces the maximum number of Lloyd’s iterations up to a stirling number order.•Experimentally, a monotone descent of the error function is consistently observed.