ADAPTIVE TRAJECTORY ANALYSIS OF REPLICATOR DYNAMICS FOR DATA CLUSTERING

摘要

A computer-implemented method for data clustering iteratively partitions a dataset into a predetermined number of clusters. At each of a plurality of iterations, replicator dynamics is performed on the objects of newly-created clusters for a predetermined number of iterations to solve an objective function. For each of these clusters, a cut-off is computed, based on a characteristic vector of the solved objective function. One of the clusters in the current set of clusters which provides most gain to the objective function when that cluster is split into two new clusters, based on the respective cut-off, is selected. The selected one of the two clusters is split into two new clusters based on the respective cut-off and the two new clusters are added to the current set of clusters. The method thus provides for different cut-offs to be used, depending on the cluster being split.