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基于约束动态更新的半监督层次聚类算法

周晨曦 梁循 齐金山

周晨曦, 梁循, 齐金山. 基于约束动态更新的半监督层次聚类算法. 自动化学报, 2015, 41(7): 1253-1263. doi: 10.16383/j.aas.2015.c140859
引用本文: 周晨曦, 梁循, 齐金山. 基于约束动态更新的半监督层次聚类算法. 自动化学报, 2015, 41(7): 1253-1263. doi: 10.16383/j.aas.2015.c140859
ZHOU Chen-Xi, LIANG Xun, QI Jin-Shan. A Semi-supervised Agglomerative Hierarchical Clustering Method Based on Dynamically Updating Constraints. ACTA AUTOMATICA SINICA, 2015, 41(7): 1253-1263. doi: 10.16383/j.aas.2015.c140859
Citation: ZHOU Chen-Xi, LIANG Xun, QI Jin-Shan. A Semi-supervised Agglomerative Hierarchical Clustering Method Based on Dynamically Updating Constraints. ACTA AUTOMATICA SINICA, 2015, 41(7): 1253-1263. doi: 10.16383/j.aas.2015.c140859

基于约束动态更新的半监督层次聚类算法

doi: 10.16383/j.aas.2015.c140859
基金项目: 

国家自然科学基金(71271211), 北京市自然科学基金(4132067),中国人民大学品牌计划(10XNI029)资助

详细信息
    作者简介:

    周晨曦中国人民大学硕士研究生. 主要研究方向为数据挖掘.E-mail: chnx.zhou@gmail.com

A Semi-supervised Agglomerative Hierarchical Clustering Method Based on Dynamically Updating Constraints

Funds: 

Supported by National Natural Science Foundation of China (71271211), National Natural Science Foundation of Beijing (4132067), and Brand Plan of Renmin University of China (10XNI029)

  • 摘要: 提出了一种基于约束动态更新的半监督层次聚类算法. 与现存的半监督层次聚类算法类似, 该算法也使用了必连和不连约束. 但不同的是, 该算法并不是在对满足必连约束的数据样本点进行预先划分的基础上依据不连约束进行聚合操作, 而是首先将约束扩展为一个闭包, 然后在这此基础上直接依据不连约束进行聚合操作, 并在聚合的过程中依据聚类结果动态地更新必连和不连约束, 以保证最终的聚类结果同时满足必连和不连约束. 该算法的优势在于省略了对必连约束的数据样本点进行预先划分的步骤, 这一改进能够保证数据样本点获得更为合理的聚合顺序, 从而得到更为准确的聚类结果. 本文具体给出了该算法基于Ward 层次聚类算法的实现, 提出了C-Ward算法.实验表明, 与其他同类算法相比, 无论是在人工模拟数据集还是在现实数据集上, 本文提出的算法都表现出了更高的准确性和更强的稳定性.
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出版历程
  • 收稿日期:  2014-12-12
  • 修回日期:  2015-03-20
  • 刊出日期:  2015-07-20

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