JSW 2009 Vol.4(4): 323-330 ISSN: 1796-217X
doi: 10.4304//jsw.4.4.323-330
doi: 10.4304//jsw.4.4.323-330
A Quantitative Method for Pulse Strength Classification Based on Decision Tree
Huiyan Wang1, Peiyong Zhang2*
1College of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China
2Institute of VLSI Design, Zhejiang University, Hangzhou, China
Abstract—Pulse diagnosis is one of the most important examinations in Traditional Chinese Medicine (TCM). In response to the subjectivity and fuzziness of pulse diagnosis in TCM, quantitative systems or methods are needed to modernize pulse diagnosis. In pulse diagnosis, strength is one of the most difficult factors to recognize. To explore the quantitative recognition of pulse strength, a novel method based on decision tree (DT) is presented. The proposed method is testified by applying it to classify four hundreds pulse signal samples collected from clinic. The results are mostly accord with the expertise, which indicate that the method we proposed is feasible and effective and can identify pulse signals accurately, which can be expected to facilitate the modernization of pulse diagnosis.
Index Terms—pulse signal identification; decision tree; feature selection; quantitative diagnosis
2Institute of VLSI Design, Zhejiang University, Hangzhou, China
Abstract—Pulse diagnosis is one of the most important examinations in Traditional Chinese Medicine (TCM). In response to the subjectivity and fuzziness of pulse diagnosis in TCM, quantitative systems or methods are needed to modernize pulse diagnosis. In pulse diagnosis, strength is one of the most difficult factors to recognize. To explore the quantitative recognition of pulse strength, a novel method based on decision tree (DT) is presented. The proposed method is testified by applying it to classify four hundreds pulse signal samples collected from clinic. The results are mostly accord with the expertise, which indicate that the method we proposed is feasible and effective and can identify pulse signals accurately, which can be expected to facilitate the modernization of pulse diagnosis.
Index Terms—pulse signal identification; decision tree; feature selection; quantitative diagnosis
Cite: Huiyan Wang, Peiyong Zhang, "A Quantitative Method for Pulse Strength Classification Based on Decision Tree," Journal of Software vol. 4, no. 4, pp. 323-330, 2009.
General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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