Parkinson’s Disease Diagnosis: Detecting the Effect of Attributes Selection and Discretization of Parkinson’s Disease Dataset on the Performance of Classifier Algorithms
Abstract:Precise detection of PD is important in its early stages. Precise result can be achieved through data mining, classification techniques such as Naïve Bayes, support vector machine (SVM), multilayer perceptron neural network (MLP) and decision tree. In this paper, four types of classifiers based on Naïve Bayes, SVM, MLP neural network, and decision tree (j48) are used to classify the PD dataset and the performances of these classifiers are examined when they are implemented upon the actual PD dataset, discretiz… Show more
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