Browsing Robust Clustering-Alternatives.

摘要: In the last years, new clustering approaches utilizing notion of multiple clusterings have gained attention. Two general directions -- each with its individual benefits are identifiable: (i) extraction alternative solutions from one dataset and (ii) combination a into robust consensussolution. this paper, we propose novel hybrid approach to generate browse robust, results. Our is based on frequent-groupings as specialization frequent-itemset mining. way, different existing combined, offering opportunities for knowledge extraction.