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

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...

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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
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Online Access:http://tckh.dlu.edu.vn/index.php/tckhdhdl/article/view/649
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author Phạm Quang Thuận
Nguyễn Đình Thuân
author_facet Phạm Quang Thuận
Nguyễn Đình Thuân
author_sort Phạm Quang Thuận
collection DOAJ
description 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.
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institution Kabale University
issn 0866-787X
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language English
publishDate 2020-09-01
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record_format Article
series Tạp chí Khoa học Đại học Đà Lạt
spelling doaj-art-3513d7d6c189454eb679c21a783ef9332025-02-02T13:08:08ZengDalat UniversityTạp chí Khoa học Đại học Đà Lạt0866-787X0866-787X2020-09-01103395110.37569/DalatUniversity.10.3.649(2020)329APPLICATION OF MACHINE LEARNING ALGORITHMS TO EVALUATE THE UCI DATABASE IN THE CLASSIFICATION OF AUTISM SPECTRUM DISORDERSPhạm Quang Thuận0Nguyễn Đình Thuân1Trường Cao đẳng Sư phạm Trung ương - Nha TrangTrường Đại học Công nghệ thông tin, Đại học Quốc gia TP.Hồ Chí Minh, Việt NamIn 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.http://tckh.dlu.edu.vn/index.php/tckhdhdl/article/view/649rối loạn phổ tự kỷsàng lọc rối loạn phổ tự kỷthuật toán học máy.
spellingShingle Phạm Quang Thuận
Nguyễn Đình Thuân
APPLICATION OF MACHINE LEARNING ALGORITHMS TO EVALUATE THE UCI DATABASE IN THE CLASSIFICATION OF AUTISM SPECTRUM DISORDERS
Tạp chí Khoa học Đại học Đà Lạt
rối loạn phổ tự kỷ
sàng lọc rối loạn phổ tự kỷ
thuật toán học máy.
title APPLICATION OF MACHINE LEARNING ALGORITHMS TO EVALUATE THE UCI DATABASE IN THE CLASSIFICATION OF AUTISM SPECTRUM DISORDERS
title_full APPLICATION OF MACHINE LEARNING ALGORITHMS TO EVALUATE THE UCI DATABASE IN THE CLASSIFICATION OF AUTISM SPECTRUM DISORDERS
title_fullStr APPLICATION OF MACHINE LEARNING ALGORITHMS TO EVALUATE THE UCI DATABASE IN THE CLASSIFICATION OF AUTISM SPECTRUM DISORDERS
title_full_unstemmed APPLICATION OF MACHINE LEARNING ALGORITHMS TO EVALUATE THE UCI DATABASE IN THE CLASSIFICATION OF AUTISM SPECTRUM DISORDERS
title_short APPLICATION OF MACHINE LEARNING ALGORITHMS TO EVALUATE THE UCI DATABASE IN THE CLASSIFICATION OF AUTISM SPECTRUM DISORDERS
title_sort application of machine learning algorithms to evaluate the uci database in the classification of autism spectrum disorders
topic rối loạn phổ tự kỷ
sàng lọc rối loạn phổ tự kỷ
thuật toán học máy.
url http://tckh.dlu.edu.vn/index.php/tckhdhdl/article/view/649
work_keys_str_mv AT phamquangthuan applicationofmachinelearningalgorithmstoevaluatetheucidatabaseintheclassificationofautismspectrumdisorders
AT nguyenđinhthuan applicationofmachinelearningalgorithmstoevaluatetheucidatabaseintheclassificationofautismspectrumdisorders