Prediction of ASD among Children using Machine Learning Techniques
Ishwaria A1, Ajaypradeep N2, Sasikala Ra3
1Ishwaria A, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
2Ajaypradeep N, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
3Dr.Sasikala Ra, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
Manuscript received on April 30, 2020. | Revised Manuscript received on May 06, 2020. | Manuscript published on May 30, 2020. | PP: 1667-1670 | Volume-9 Issue-1, May 2020. | Retrieval Number: A2455059120/2020©BEIESP | DOI: 10.35940/ijrte.A2455.059120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Autism spectrum disorder (ASD) is a neurological issue that begins from early in childhood and proceeds all through such an individual’s reality. It will influence that individual’s conduct, speech with others, interference, and learning. Right now anyway, Autism Spectrum Disorder is to be distinguished in the beginning period, which is conceivable. Early acknowledgment of Autism Spectrum Disorder will improve the general psychological wellness of that particular youngster. The machine learning methodology is applied to diagnose Autism Spectrum Disorder (ASD), and in this work, we have used machine learning techniques and Optimization on an ASD dataset. We have employed XGBoost algorithms to the dataset considered, and as a result, efficient outputs are obtained. This will be incredible for the use of doctors to help them recognize Autism Spectrum Disorder at an early prior stage.
Keywords: ASD, Machine Learning, XG Boost..
Scope of the Article: Machine Learning