Adaptive Clustering and Multidimensional Scaling of Large and Highdimensional Data Sets

We describe a algorithm for exploratory data analysis which combines the adaptive c-means clustering and the multi-dimensional scaling procedure (ACMMDS). ACMMDS is an algorithm for the online visualization of clustering processes and may be considered as a alternative approach to Kohonen’s self organizing feature (SOM). Whereas SOM is a heuristic neural network algorithm, ACMMDS is derived from multivariate statistic algorithms. The possible implications of ACMMDS are illustrated through two different data sets.