RAIN: data clustering using randomized interactions between data points

This paper introduces a generalization of the Gravitational Clustering Algorithm. First, it is extended in such a way that the Gravitational Law is not the only law that can be applied. Instead, any decreasing function of the distance between points can be used. An estimate of the maximum distance between the closest points is calculated in order to reduce the sensibility of the clustering process to the size of the data set. Finally, a heuristic for setting the interaction strength (gravitational constant) is introduced in order to reduce the number of parameters of the algorithm. Experiments with benchmark synthetic data sets are performed in order to show the applicability of the proposed approach.