半监督聚类中成对约束的主动学习OA北大核心CSTPCD
Active Learning of Pair-wise Constraints in Semi-supervised Clustering
本文提出一种纠错式主动学习成对约束的方法,探讨了主动学习的停止条件,在较少的约束下可得到较好的聚类结果.通过在UCI基准数据集以及人工数据集的实验表明,在该学习策略下,半监督聚类算法的性能好于对比算法;在停止条件下,每个数据集的聚类结果都是可接受的.
An active learning method of pair-wise constraints based on error correction is proposed in this paper,and stopping criterion is also presented in order to get better clustering result with less pair-wise constraints. Experiments on the UCI benchmark datasets and artificial datasets show that the performance of semi-supervised clustering algorithm with the proposed strategy is better than that of compared strategies. In addition,the clustering result of each…查看全部>>
杨洋;王立宏
烟台大学,计算机学院,山东,烟台,264005烟台大学,计算机学院,山东,烟台,264005
信息技术与安全科学
半监督聚类主动式学习监督信息
semi-supervised clustering ；active learning ；supervision information
《广西师范大学学报（自然科学版）》 2011 (1)
功能性非编码序列多样性分析及其在外源高效表达基因载体的设计研究
87-91,5
国家自然科学基金资助项目(61070118)
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