• Rashmi S R
• Dr.Uma B

In present day Autism Spectrum Disorder (ASD) is gaining its momentum faster than ever. Detecting autism traits through screening tests is very expensive and time consuming. With the advancement of artificial intelligence and machine learning (ML), autism can be predicted at quite early stage. Though number of studies have been carried out using different techniques, these studies didn’t provide any definitive conclusion about predicting autism traits in terms of different age groups. The proposed model was evaluated with AQ- 10 dataset and 1000 real dataset collected from people with and without autistic traits. The evaluation results showed that the proposed prediction model provide better results in terms of accuracy, specificity, sensitivity, precision and false positive rate (FPR) for both kinds of datasets.

Machine Learning, Random Forest, Support Vector Machine, Adaboost.

"A Machine Learning Approach to Predict Autism Spectrum Disorder", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.232-235, June 2019, Available :http://www.jetir.org/papers/JETIR1907Q78.pdf

"A Machine Learning Approach to Predict Autism Spectrum Disorder", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp232-235, June 2019, Available at : http://www.jetir.org/papers/JETIR1907Q78.pdf