Analysis of Autism Spectrum Disorder Prediction using various Machine Learning Models

The incidence of Autism in India has been on the rise, with reference to the recent studies the frequency of occurrence is approximately 1 in 68 children. However, early diagnosis and intervention remain insufficient, leading to many children lacking timely support. Early detection plays a vital role in empowering individuals with Autism Spectrum Disorder (ASD) to lead satisfying lives. Hence an extensive analysis has been done to validate the efficiency of various machine learning models in estimatingASD. It has been observed from the analysis that diverse models, including Support Vector Machine (SVM), K Nearest Neighbor (KNN), Decision Tree (DT), Random Forest(RF), and Deep Neural Network (DNN), demonstrate promising results in estimating ASD.