Visualizing fuzzy points in parallel coordinates

Exploratory data analysis heavily relies on methods to visualize data and models in a user friendly and interpretable manner. We show how models consisting of a collection of fuzzy points can be visualized in parallel coordinates. In contrast to existing techniques that display only lines representing centroids or shaded areas showing the general variance of cluster centers, the proposed technique shows the spread of the fuzzy membership in each dimension in detail. This allows for a better interpretation of overlap in fuzzy rules.