Enhanced of autism spectrum disorder using grey relational analysis and supervised learning for classification
Autism spectrum disorder (ASD) is complicated to be diagnosed and many study had shown that machine learning technique have been proven to accurately diagnose ASD. However, there were also some drawbacks in the results obtained and one of it is related to the lower accuracy upon implementation. Thus...
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2020
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| Online Access: | http://eprints.utm.my/id/eprint/93599/1/ZuriahatiMohdYunos2020_EnhancedofAutismSpectrumDisorder.pdf http://eprints.utm.my/id/eprint/93599/ http://dx.doi.org/10.1088/1757-899X/864/1/012083 |
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my.utm.935992021-12-31T07:34:48Z http://eprints.utm.my/id/eprint/93599/ Enhanced of autism spectrum disorder using grey relational analysis and supervised learning for classification Mohd. Yunos, Z. Idrus, W. Shamsuddin, S. M. Saadon, M. S. I. M. Yusuf, S. QA75 Electronic computers. Computer science Autism spectrum disorder (ASD) is complicated to be diagnosed and many study had shown that machine learning technique have been proven to accurately diagnose ASD. However, there were also some drawbacks in the results obtained and one of it is related to the lower accuracy upon implementation. Thus, a feature selection method namely Grey Relational Analysis (GRA) is proposed to enhance the performance of the machine learning technique in the classification of ASD as it was proven too often produce high accuracy results. GRA is used to select relevant features and rank them from the highest to the lowest. The data used was the adult autism data, which consists of 608 data with 16 features. The machine learning techniques used are Support Vector Machine (SVM) and Artificial Neural Network with Multi Layer Perceptron (ANN-MLP) to classify ASD. From results obtained, the integration of GRA and machine learning techniques have managed to produce a high accuracy of more than 90%. The SVM gave the good accuracy of 98.1%, while ANN produce of 98.36% 2020 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/93599/1/ZuriahatiMohdYunos2020_EnhancedofAutismSpectrumDisorder.pdf Mohd. Yunos, Z. and Idrus, W. and Shamsuddin, S. M. and Saadon, M. S. I. and M. Yusuf, S. (2020) Enhanced of autism spectrum disorder using grey relational analysis and supervised learning for classification. In: 2nd Joint Conference on Green Engineering Technology and Applied Computing 2020, IConGETech 2020 and International Conference on Applied Computing 2020, ICAC 2020, 4-5 Feb 2020, Bangkok, Thailand. http://dx.doi.org/10.1088/1757-899X/864/1/012083 |
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QA75 Electronic computers. Computer science Mohd. Yunos, Z. Idrus, W. Shamsuddin, S. M. Saadon, M. S. I. M. Yusuf, S. Enhanced of autism spectrum disorder using grey relational analysis and supervised learning for classification |
| description |
Autism spectrum disorder (ASD) is complicated to be diagnosed and many study had shown that machine learning technique have been proven to accurately diagnose ASD. However, there were also some drawbacks in the results obtained and one of it is related to the lower accuracy upon implementation. Thus, a feature selection method namely Grey Relational Analysis (GRA) is proposed to enhance the performance of the machine learning technique in the classification of ASD as it was proven too often produce high accuracy results. GRA is used to select relevant features and rank them from the highest to the lowest. The data used was the adult autism data, which consists of 608 data with 16 features. The machine learning techniques used are Support Vector Machine (SVM) and Artificial Neural Network with Multi Layer Perceptron (ANN-MLP) to classify ASD. From results obtained, the integration of GRA and machine learning techniques have managed to produce a high accuracy of more than 90%. The SVM gave the good accuracy of 98.1%, while ANN produce of 98.36% |
| format |
Conference or Workshop Item |
| author |
Mohd. Yunos, Z. Idrus, W. Shamsuddin, S. M. Saadon, M. S. I. M. Yusuf, S. |
| author_facet |
Mohd. Yunos, Z. Idrus, W. Shamsuddin, S. M. Saadon, M. S. I. M. Yusuf, S. |
| author_sort |
Mohd. Yunos, Z. |
| title |
Enhanced of autism spectrum disorder using grey relational analysis and supervised learning for classification |
| title_short |
Enhanced of autism spectrum disorder using grey relational analysis and supervised learning for classification |
| title_full |
Enhanced of autism spectrum disorder using grey relational analysis and supervised learning for classification |
| title_fullStr |
Enhanced of autism spectrum disorder using grey relational analysis and supervised learning for classification |
| title_full_unstemmed |
Enhanced of autism spectrum disorder using grey relational analysis and supervised learning for classification |
| title_sort |
enhanced of autism spectrum disorder using grey relational analysis and supervised learning for classification |
| publishDate |
2020 |
| url |
http://eprints.utm.my/id/eprint/93599/1/ZuriahatiMohdYunos2020_EnhancedofAutismSpectrumDisorder.pdf http://eprints.utm.my/id/eprint/93599/ http://dx.doi.org/10.1088/1757-899X/864/1/012083 |
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1720980097764163584 |
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13.211869 |