Visualizing Fuzzy Clusters Using RadViz
John Sharko, Georges Grinstein · 2009
Clustering techniques are heuristic processes that typically do not yield one optimal solution. Therefore it is common practice to generate multiple cluster sets and investigate the consistency of the record groupings. Fuzzy clustering essentially achieves the same objective by providing a measure of the extent to which each record belongs to each cluster i.e. the strength of association of each record to each cluster. This paper develops a visualization of fuzzy clustering using RadViz, compares it to a Vectorized RadViz visualization of the results of multiple cluster ensembles and then applies it to a microarray dataset.