In this paper, we propose a new clustering procedure for high dimensional microarray data. Major difficulty in cluster analysis of microarray data is that the number of samples to ...
Abstract. In many situations, high dimensional data can be considered as sampled functions. We show in this paper how to implement a Self-Organizing Map (SOM) on such data by appro...
When data resides on tertiary storage, clustering is the key to achieving high retrieval performance. However, a straightforward approach to clustering massive amounts of data on ...
Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special p...
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...