Shi-Hua Liu, Liang-Zhong Shen, De-Cai Huang, "A Three-Stage Framework for Clustering Mixed Data," WSEAS Transactions on Systems, vol. 15, pp. 1-10, 2016, DOI:
Shi-Hua Liu, Liang-Zhong Shen, De-Cai Huang. A Three-Stage Framework for Clustering Mixed Data.
WSEAS Transactions on Systems. 2016;15:1-10.
WSEAS Transactions on Systems
Print ISSN: 1109-2777, E-ISSN: 2224-2678
Volume 15, 2016
A Three-Stage Framework for Clustering Mixed Data
Authors: , ,
Abstract: A three-stage framework and a simple implemented algorithm for clustering mixed data are proposed. In the framework, the mixed dataset is divided into several subsets according to the different types of attributes, and each subset is clustered using according off-the-shelf algorithms, the results are combined as a new categorical dataset and then be clustered. The final result is the answer for clustering the original mixed dataset. The experimental results show that the proposed framework and the implemented algorithm can be used to cluster the mixed dataset efficiently and it is prior to the k-prototypes.
Keywords:
Clustering mixed data, Cluster ensemble, Clustering principle, k-prototypes, kMM algorithm
Pages: 1-10 WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 15, 2016, Art. #1 DOI: *As the DOI is a unique identifier, it is already available in the pdf version.
**The DOI link will be activated in the first midst of January 2026.
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