基于网格最小生成树的聚类算法选择

摘要

To get better clustering results, it is necessary to choose a suitable clustering algorithm for the cluster structure of a given dataset. Selection of clustering algorithms based on Grid-MST is proposed to choose a suitable clustering algorithm for the data set automatically. The Grid-MST is constructed on the basis of the dataset by the proposed method, and the potential cluster structures are found by the number of trees. Then, a suitable clustering algorithm is selected to the discovered cluster structure. The experimental results on artificial datasets and real datasets show that the proposed method is efficient.%为得到好的聚类效果,需要挑选适合数据集簇结构的聚类算法.文中提出基于网格最小生成树的聚类算法选择方法,为给定数据集自动选择适合的聚类算法.该方法首先在数据集上构建出网格最小生成树,由树的数目确定数据集的潜在簇结构,然后为数据集选择适合所发现簇结构的聚类算法.实验结果表明该方法较有效,能为给定数据集找出适合其潜在簇结构的聚类算法.