山东大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (2): 1-9.doi: 10.6040/j.issn.1672-3961.1.2014.095
• 机器学习与数据挖掘 • 下一篇
董红斌, 张广江, 逄锦伟, 韩启龙
DONG Hongbin, ZHANG Guangjiang, PANG Jinwei, HAN Qilong
摘要: 针对单一聚类算法存在的不能泛化的问题,将集成学习技术应用于聚类算法中,集成学习技术可以显著提高学习系统的泛化能力。提出了1种基于粒子群和遗传算法的协同进化聚类集成算法,粒子群算法保证算法快速收敛,遗传算法全局搜索扩大搜索范围,提高了聚类的性能和收敛速度。将本研究提出的算法在多个UCI数据集上进行试验验证,结果表明该算法是有效的。
中图分类号:
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