Universiti Teknologi Malaysia Institutional Repository

Classification of adult autistic spectrum disorder using machine learning approach

Mashudi, Nurul Amirah and Ahmad, Norulhusna and Mohd. Noor, Norliza (2021) Classification of adult autistic spectrum disorder using machine learning approach. IAES International Journal of Artificial Intelligence, 10 (3). pp. 743-751. ISSN 2089-4872


Official URL: http://dx.doi.org/10.11591/ijai.v10.i3.pp743-751


Autism spectrum disorder (ASD) is a neurological-related disorder. Patients with ASD have poor social interaction and lack of communication that lead to restricted activities. Thus, early diagnosis with a reliable system is crucial as the symptoms may affect the patient’s entire lifetime. Machine learning approaches are an effective and efficient method for the prediction of ASD disease. The study mainly aims to achieve the accuracy of ASD classification using a variety of machine learning approaches. The dataset comprises 16 selected attributes that are inclusive of 703 patients and non-patients. The experiments are performed within the simulation environment and analyzed using the Waikato environment for knowledge analysis (WEKA) platform. Linear support vector machine (SVM), k-nearest neighbours (k-NN), J48, Bagging, Stacking, AdaBoost, and naïve bayes are the methods used to compute the prediction of ASD status on the subject using 3, 5, and 10-folds cross validation. The analysis is then computed to evaluate the accuracy, sensitivity, and specificity of the proposed methods. The comparative result between the machine learning approaches has shown that linear SVM, J48, Bagging, Stacking, and naïve bayes produce the highest accuracy at 100% with the lowest error rate.

Item Type:Article
Uncontrolled Keywords:Autism spectrum disorder, Classification, Machine learning
Subjects:T Technology > T Technology (General)
Divisions:Razak School of Engineering and Advanced Technology
ID Code:96730
Deposited By: Widya Wahid
Deposited On:20 Aug 2022 09:43
Last Modified:20 Aug 2022 09:43

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