Abstract

Autism Spectrum Disorder (ASD) is a developmental disability caused by differences in brain. Scientists believe there are multiple causes of ASD that act together to change the most common ways people develop. The diagnosis process for ASD must be early to provide the required clinical and mental care. In this paper, Machine Learning classifiers were applied using data mining techniques to develop a prediction model for ASD. The dataset utilized comprised 507 instances of children aged between 12 and 36 months. The experimental results show that all classifiers Logistic Regression (LR), Support Vector Machine (SVM), Decision tree, Naïve Bayes, and Artificial Neural Network (ANN) have an excellent accuracy between 95% to 100%. Furthermore, LR, SVM, and ANN have 100% accuracy.

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