关键词: 混合属性, 松弛聚类算法, 自适应, 聚类集成, 鲁棒性

Abstract: Based on the problem analysis on existing mixed data clustering algorithms, the graph-based relaxed clustering algorithm is used as the problem solving foundation. Introduced the gaussian kernel parameter self-adapting computing step, the graph-based relaxed clustering algorithm is improved on the foundation of the “Local Scale” idea, and the points distance calculating process is extended to the mixed data clustering. Moreover, depended on the previous improved steps and cluster ensemble technology, a new mixed data clustering algorithm is proposed. Lastly, the case experiments are completed, and the results prove that the new algorithm has high robustness and good cluster precision.

Key words: mixed attribute, relaxed clustering algorithm, self-adapting, cluster ensemble, robustness