Classification of Neurodegenerative Diseases using Machine Learning Methods - Aydin, Fatih; Aslan, Zafer (International Journal of Intelligent Systems and Applications in Engineering, 2017)
In this study, neurodegenerative diseases (Amyotrophic Lateral Sclerosis, Huntingtonâs disease, and Parkinsonâs disease) were diagnosed and classified using force signals.Â  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.