Semi-Automatic Visual Subgroup Mining using VIKAMINE
Martin Atzmueller (University of Würzburg, Germany)
Frank Puppe (University of Würzburg, Germany)
Abstract: Visual mining methods enable the direct integration of the user to overcome major problems of automatic data mining methods, e.g., the presentation of uninteresting results, lack of acceptance of the discovered findings, or limited confidence in these. We present a novel subgroup mining approach for explorative and descriptive data mining implemented in the VIKAMINE system. We propose several integrated visualization methods to support subgroup mining. Furthermore, we describe three case studies using data from fielded systems in the medical domain.
Keywords: data analysis, data mining, subgroup mining, visualization
Categories: H.5.1, H.5.2, I.2.1, I.2.6