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http://dx.doi.org/10.7472/jksii.2014.15.3.109

Classification of Parkinson's Disease Using Defuzzification-Based Instance Selection  

Lee, Sang-Hong (Department of Computer Science & Engineering, Anyang University)
Publication Information
Journal of Internet Computing and Services / v.15, no.3, 2014 , pp. 109-116 More about this Journal
Abstract
This study proposed new instance selection using neural network with weighted fuzzy membership functions(NEWFM) based on Takagi-Sugeno(T-S) fuzzy model to improve the classification performance. The proposed instance selection adopted weighted average defuzzification of the T-S fuzzy model and an interval selection, same as the confidence interval in a normal distribution used in statistics. In order to evaluate the classification performance of the proposed instance selection, the results were compared with depending on whether to use instance selection from the case study. The classification performances of depending on whether to use instance selection show 77.33% and 78.19%, respectively. Also, to show the difference between the classification performance of depending on whether to use instance selection, a statistics methodology, McNemar test, was used. The test results showed that the instance selection was superior to no instance selection as the significance level was lower than 0.05.
Keywords
Instance Selection; Parkinson's Disease; Gait; Fuzzy Neural Networks; Wavelet Transforms; Normal Distribution;
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Times Cited By KSCI : 2  (Citation Analysis)
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