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JACIII Vol.8 No.6 pp. 599-605
doi: 10.20965/jaciii.2004.p0599
(2004)

Paper:

Comparison of Linguistic and Regular Hard C-Means in Postoperative Patient Data

Sansanee Auephanwiriyakul*, and Nipon Theera-Umpon**

*Computer Engineering Department, Chiang Mai University, Chiang Mai 50200, Thailand

**Electrical Engineering Department, Chiang Mai University, Chiang Mai 50200, Thailand

Received:
July 30, 2004
Accepted:
September 12, 2004
Published:
November 20, 2004
Keywords:
linguistic hard c-means, hard c-means, postoperative
Abstract

Classification is one of the main topics in pattern recognition. Generally, classification problems deal with numeric data. However, there are uncertainties in the data frequently, such as data collected in management questionnaires, postoperative patient data, etc. Hence, classification problems on linguistic data are challenging. In this paper, we compare the performance of the linguistic Hard C-Means (LHCM) with the regular Hard C-Means (HCM) through the postoperative patient data. We found that the LHCM performs better than the regular HCM in terms of the classification rate. In addition, we are able to interpret each cluster attribute by the input linguistic label.

Cite this article as:
S. Auephanwiriyakul and N. Theera-Umpon, “Comparison of Linguistic and Regular Hard C-Means in Postoperative Patient Data,” J. Adv. Comput. Intell. Intell. Inform., Vol.8, No.6, pp. 599-605, 2004.
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Last updated on Sep. 09, 2019