Visualizing membership in multiple clusters after fuzzy c-means clustering

摘要

Cluster analysis is an exploratory data mining technique that involves grouping data points together based on their similarity. Objects or data points are often similar to points in more than one cluster; this is typically quantified by a measure of membership in a cluster, called fuzziness. Visualizing membership degrees in multiple clusters is the main topic of this paper. We use Orca, a java-based high-dimensional visualization environment, as the implementation platform to test several approaches, including convex hulls, glyphs, coloring schemes, and 3-dimensional plots.