APPLYING MACHINE LEARNING TECHNIQUES TO PREDICT AUTSIM SPECTRUM DISORDER
Nowadays Autism Spectrum Disorder (ASD) is gaining its momentum faster than ever, with the advancement of artificial intelligence, autism can be predicted at quite early stage. This paper aims to propose an effective prediction approach using autism dataset after preprocessing to be suitable with the algorithms to reach the best result. This dataset applied on seven machine learning algorithms: K Nearest Neighbor algorithm, Random Forest algorithm, Decision Tree algorithm, Multilayer Perceptron algorithm, Naive Bayes, AdaBoost, and Gradient Boosting algorithm. The evaluation metrics that will be relied upon in this research and the comparison between the performances of the applied algorithms is: recall, accuracy, precision, and f1-score.
classification, machine learning, Autism.