Zheng Classification with Missing Feature Values Using Local-Validity Approach
Joint Authors
Source
Evidence-Based Complementary and Alternative Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-23
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Zheng classification is a very important step in the diagnosis of traditional Chinese medicine (TCM).
In clinical practice of TCM, feature values are often missing and incomplete cases.
The performance of Zheng classification is strictly related to rates of missing feature values.
Based on the pattern of the missing feature values, a new approach named local-validity is proposed to classify zheng classification with missing feature values.
Firstly, the maximum submatrix for the given dataset is constructed and local-validity method finds subsets of cases for which all of the feature values are available.
To reduce the computational scale and improve the classification accuracy, the method clusters subsets with similar patterns to form local-validity subsets.
Finally, the proposed method trains a classifier for each local-validity subset and combines the outputs of individual classifiers to diagnose zheng classification.
The proposed method is applied to the real liver cirrhosis dataset and three public datasets.
Experimental results show that classification performance of local-validity method is superior to the widely used methods under missing feature values.
American Psychological Association (APA)
Wang, Yan& Ma, Li Zhuang. 2013. Zheng Classification with Missing Feature Values Using Local-Validity Approach. Evidence-Based Complementary and Alternative Medicine،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-476072
Modern Language Association (MLA)
Wang, Yan& Ma, Li Zhuang. Zheng Classification with Missing Feature Values Using Local-Validity Approach. Evidence-Based Complementary and Alternative Medicine No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-476072
American Medical Association (AMA)
Wang, Yan& Ma, Li Zhuang. Zheng Classification with Missing Feature Values Using Local-Validity Approach. Evidence-Based Complementary and Alternative Medicine. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-476072
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-476072