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OALib Journal期刊
ISSN: 2333-9721
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？面向不确定数据的近似骨架启发式聚类算法
DOI: 10.13232/j.cnki.j nju.2015.01.027, PP. 197-205
Keywords: np-难解,启发式算法,近似骨架,不确定数据聚类
Abstract:
？不确定数据聚类是传统数据挖掘的扩展，面对不确定数据聚类，研究者们经常把聚类问题描述成组合优化问题，并设计启发式聚类算法进行求解。现有的启发式聚类算法，如uk-means和uk-medoids具有容易理解和实现简单等优点，但初始解敏感问题严重影响了聚类质量。本文在近似骨架理论的基础上，提出了一种近似骨架启发式聚类算法appgcu(approximatebackboneguidedheuristicclusteringalgorithmforuncertaindata)。该算法首先对原数据集完成p次采样，在采样后的规模较小的p个数据集上分别执行uk-medoids算法得到p个局部最优解；然后通过对p个局部最优解求交得到近似骨架，并从中提取初始簇心；最后从初始簇心开始，启发式搜索出聚类结果。在仿真和实际数据集中的实验结果表明，算法appgcu的聚类结果明显高于实验对比的启发式聚类算法，提高了聚类质量。？
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