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All Journal International Journal of Intelligent Systems and Applications in Engineering
Aydin, Fatih
Advanced Technology and Science (ATScience)
Computer Science & IT

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Classification of Neurodegenerative Diseases using Machine Learning Methods Aydin, Fatih; Aslan, Zafer
International Journal of Intelligent Systems and Applications in Engineering Vol 5, No 1 (2017)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2017526689

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.
Co-Authors Aslan, Zafer