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Performance Comparison of Algorithm through Classification of Parkinson`s Disease According to the Speech Feature
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 Title & Authors
Performance Comparison of Algorithm through Classification of Parkinson`s Disease According to the Speech Feature
Chung, Jae Woo;
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 Abstract
The purpose of this study was to classify healty persons and Parkinson disease patients from the vocal characteristics of healty persons and the of Parkinson disease patients using Machine Learning algorithms. So, we compared the most widely used algorithms for Machine Learning such as J48 algorithm and REPTree algorithm. In order to evaluate the classification performance of the two algorithms, the results were compared with depending on vocal characteristics. The classification performance of depending on vocal characteristics show 88.72% and 84.62%. The test results showed that the J48 algorithms was superior to REPTree algorithms.
 Keywords
Data Mining;Weka;Machine Learning;Algorithm;Parkinson`s disease;
 Language
Korean
 Cited by
1.
Classification of Parkinson’s disease utilizing multi-edit nearest-neighbor and ensemble learning algorithms with speech samples, BioMedical Engineering OnLine, 2016, 15, 1  crossref(new windwow)
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