Milligan G W
Multivariate Behav Res. 1981 Jul 1;16(3):379-407. doi: 10.1207/s15327906mbr1603_7.
A review of Monte Carlo validation studies of clustering algorithms is presented. Several validation studies have tended to support the view that Ward's minimum variance hierarchical method gives the best recovery of cluster structure. However, a more complete review of the validation literature on clustering indicates that other algorithms may provide better recovery under a variety of conditions. Applied researchers are cautioned concerning the uncritical selection of Ward's method for empirical research. Alternative explanations for the differential recovery performance are explored and recommendations are made for future Monte Carlo experiments.
本文对聚类算法的蒙特卡洛验证研究进行了综述。多项验证研究倾向于支持这样一种观点，即沃德最小方差层次方法能最好地恢复聚类结构。然而，对聚类验证文献更全面的综述表明，在各种条件下其他算法可能会提供更好的恢复效果。对于在实证研究中不加批判地选择沃德方法的应用研究人员提出了警告。探讨了差异恢复性能的其他解释，并对未来的蒙特卡洛实验提出了建议。
