An On-Line Agglomerative Clustering Method for Nonstationary Data

摘要

An on-line agglomerative clustering algorithm for nonstationary data is described. Three issues are addressed. The first regards the temporal as- pects of the data. The clustering of stationary data by the proposed al- gorithm is comparable to the other popular algorithms tested (batch and on-line). The second issue addressed is the number of clusters required to represent the data. The algorithm provides an efficient framework to determine the natural number of clusters given the scale of the problem.