RAIN: data clustering using randomized interactions between data points

Abstract-- This paper introduces a generalization of the Gravitational Clustering Algorithm proposed by Gomez et all in [1]. First, it is extended in such a way that not only the Gravitational Law can be applied but any decreasing function of the distance between points can be used. An estimate of the maximum distance between closest points is calculated in order to reduce the sensibility of the clustering process to the size of the data set. Finally, an heuristic for setting the interaction strength (gravitational constant) is introduced in order to reduce the number of parameters of the algorithm. Experiments with well known synthetic data sets are performed in order to show the applicability of the proposed approach.

• Type: Conference
• Year: 2004
• Where: ICMLA
• Authors: Jonatan Gómez, Olfa Nasraoui, Elizabeth Leon
• Keywords: Data Sets, Gravitational Clustering Algorithm, Gravitational Law, ICMLA 2004, ICMLA 2007