贾俊芳, 李德玉. 一种有效的高维分类数据聚类方法研究[J]. 微电子学与计算机, 2011, 28(6): 88-91.
引用本文: 贾俊芳, 李德玉. 一种有效的高维分类数据聚类方法研究[J]. 微电子学与计算机, 2011, 28(6): 88-91.
JIA Jun-fang, LI De-yu. An Effective High Dimensional Categorical Data Clustering Method Research[J]. Microelectronics & Computer, 2011, 28(6): 88-91.
Citation: JIA Jun-fang, LI De-yu. An Effective High Dimensional Categorical Data Clustering Method Research[J]. Microelectronics & Computer, 2011, 28(6): 88-91.

一种有效的高维分类数据聚类方法研究

An Effective High Dimensional Categorical Data Clustering Method Research

  • 摘要: 随着数据规模的不断增大, 提高K-modes聚类算法或模糊K-modes聚类算法的运行效率成为了一个重要问题.为了提高其算法执行效率, 提出了一种基于分治法的高维分类数据聚类方法.该方法并不是一次性对所有的数据进行聚类, 而是将分类数据集分成若干个子集, 对每个子集同时进行聚类, 最后对聚类结果进行融合以形成最终的聚类结果.实验结果表明大多数情况下较传统的方法在聚类的速度上有显著的提高.

     

    Abstract: With the increasing size of data set, improving the efficiency of K-modes clustering algorithm or fuzzy K-modes clustering algorithm is becoming a critical issue.In order to improve the efficiency of the algorithm, a clustering method based on divided and conquered method was proposed.This method, not a one-time clustering of all data, divided the data set into several subsets, and each subset was clustered at the same time;the fusion results of each subset cluster form the final clustering results.The results show that the efficiency of clustering has been increased greatly compared with traditional clustering method in most cases.

     

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