Enhancing
Interactive Visual Data Analysis
by
Statistical Functionality

Both information visualization and statistics analyse high dimensional data, but these sciences apply different systems to explore datasets. While techniques of the former field makes use of the user's pattern recognition skills, statistical algorithms apply the capabilities of computers. Based on this observation an interactive combination of techniques of both sciences can help to overcome their drawbacks. For this purpose a library was compiled that contains statistical routines, which are of high importance for information visualization techniques and allow a fast modification of their results, to integrate possible adaptations in the interactive visual data mining process.

Keywords: Data Mining, Information Visualization, Clustering, Dimension Reduction, Outlier Detection

Paper