Prediction Of Covid-19 Infection Based on Lifestyle Habits Employing Random Forest Algorithm

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Farooq Sunar Mahammad, P. Bhaskar, A Prudvi, N Yugandhar Reddy, P Jaswanth Reddy, Harshavardhan, S Mahammad Ali


A data of four factors contributing to covid-19 infection and whether the person has been infected or not is taken as input to train a Random Forest Algorithm. Factors like wearing mask, regularity of exercise, consumption of pepper and area population density are taken as input factors and the status of covid-19 infection is taken as output parameter. A random forest model trained with at least 50 data instances will become a powerful predictive model for assessing the risk of covid-19 infection.  

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