计算机科学 ›› 2015, Vol. 42 ›› Issue (7): 48-51.doi: 10.11896/j.issn.1002-137X.2015.07.011
孟晓龙 杨 燕 王红军 肖文超
MENG Xiao-long YANG Yan WANG Hong-jun XIAO Wen-chao
摘要: 使用集成学习技术可以提高聚类性能。在实验中发现,当各聚类成员聚类迭代到中后期时进行集成所得的结果会优于其迭代完全停止时进行集成所得的结果。利用集成网络泛化能力的偏差-方差分解理论对聚类集成过程中的上述现象进行解释,将提高集成网络间泛化能力的早期停止准则应用于聚类集成过程,并提出聚类集成时机的概念。对比实验表明,基于早期停止准则的聚类集成得到的结果较好,且更节约聚类集成的时间,为寻求聚类集成的最佳时机提供了可行性建议和方法。
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