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)

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.