APPLICATION OF MACHINE LEARNING ALGORITHMS TO EVALUATE THE UCI DATABASE IN THE CLASSIFICATION OF AUTISM SPECTRUM DISORDERS

• Main Authors: Phạm Quang Thuận, Nguyễn Đình Thuân
• Format: Article
• Language: English
• Published: Dalat University 2020-09-01
• Series: Tạp chí Khoa học Đại học Đà Lạt
• Subjects: rối loạn phổ tự kỷ; sàng lọc rối loạn phổ tự kỷ; thuật toán học máy.
• Online Access: http://tckh.dlu.edu.vn/index.php/tckhdhdl/article/view/649

In this article, we present the results of an evaluation of the autism spectrum disorder classification (ASD) of children in the UCI database. We evaluated the data set with the SVM and Random Forest algorithms and also investigated the Decision Tree, Logistic Regression, K-Nearest-Neighbors, Naïve Bayes, and Multi-Layer Perceptron (MLP) algorithms. All algorithms give high classification results consistent with previous studies. We conclude that the data set for classifying children's autism spectrum disorders in the UCI database is reliable.