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Autism Spectrum Disorder is a lifelong brain developmental disorder. Diagnosing the level of Autism and predicting the severity of the same are too complex, and it requires a depth analysis of the historical data on the autism patient. Nowadays, Data science techniques play a vital role in diagnosing autism. Decision Tree, Random Forest, Logistic Regression, Adaboost, Naïve Bayse, K-Nearest Neighbour, Support Vector Machine and etc., are the few techniques labeled under the roof of data science are used to predict such disorders.   The paper aims to present a survey on the various models proposed by various researchers to predict the severity of autism using data science techniques.



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Author Biography


Research Scholar, Department of Computer Science, Periyar E.V.R College (Autonomous), Tiruchirappalli, Tamil Nadu, India.


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