Double Versus Optimal Grade Clusterings
Two clustering methods based on grade correspondence analysis will be compared on a real data example. Special attention will be paid to the interpretation aspects versus the formal inference based on clustering quality measures. The discussed example shows that formally similar solutions may differ significantly from the interpretation point of view.
Unable to display preview. Download preview PDF.
- CIOK, A. (1998): Discretization as a tool in cluster analysis. In: A. Rizzi, M. Vichi, and H.-H. Bock (Eds.): Advances in Data Science and Classification. Springer, Heidelberg, 349–354.Google Scholar
- CIOK, A., KOWALCZYK, T., PLESZCZYNSKA, E., SZCZESNY, W. (1998): How a new statistical infrastructure induced a new computing trend in data analysis. In: L. Polkowski, A. Skowron (Eds.): Rough sets and current trends in computing. Lecture Notes in Artificial Intelligence 1424, Springer, 75–82Google Scholar