A Monte Carlo Evaluation of the Moving Method, K-means and Two Self-Organising Neural Networks

摘要

In recent years there has been increasing interest in the comparative clustering abilities of k-means, moving methods and self- organising neural networks. However, most comparative studies have either been restricted to specific problem areas or have been conducted with other limitations that do not provide a more general evaluation of the relative abilities of these methods under a wide variety of conditions. This report provides a systematic empirical evaluation of the clustering abilities of k-means, moving methods and two commonly used self-organising neural network architectures.