Classification of Neurodegenerative Diseases using Machine Learning Methods
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2017, Vol 5, Issue 1
Abstract
In this study, neurodegenerative diseases (Amyotrophic Lateral Sclerosis, Huntington’s disease, and Parkinson’s disease) were diagnosed and classified using force signals. In the classification, five machine learning algorithms (Averaged 2-Dependence Estimators (A2DE), K* (K star), Multilayer Perceptron (MLP), Diverse Ensemble Creation by Oppositional Relabeling of Artificial Training Examples (DECORATE), Random Forest) were compared by the 10-fold Cross Validation method. K* classifier gave the best outcome among these algorithms. As a result of quad classification of the K* classifier, the best classification accuracy was 99.17%. According to the first three and five principal component qualifications which are created from these 19 features, the best classification accuracies of K* classifier were 95.44% and 96.68% respectively.
Authors and Affiliations
Fatih Aydin*| fatih.aydin@klu.edu.tr, Zafer Aslan| Computer Engineering, Faculty of Engineering, Istanbul Aydin University,
Keywords
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- EP ID EP814
- DOI 10.18201/ijisae.2017526689
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