A COVID-19 PREDICTION BASED on MACHINE LEARNING ALGORITHMS - A LITERATURE REVIEW

ABSTRACT

The SAR.CoV2 disease 2019(covid-19) pandemic affected many countries of the world. Actually, almost all the countries presented Covid-19 positive cases and governments are choosing different health policies to stop the infection and many programs are conducted with aware common people. Then number of positive cases increasing rapidly everyday around the world. This paper is going to propose a prediction on what basis common people getting affected and how to reduce the spreading of disease. Machine learning algorithms have been used in all the fields in predicting. Especially in medicine and enriches the applications of machine learning which are accurate and robust in selecting attributes. Here we investigate some of the machine learning models namely Decision Tree, Random Forest, Adaboost and Logistic Regression to predict accuracy of getting affected. In our experiment shows prediction result accuracies 70.1, 70.3, 67.9, 70.6 respectively. © 2022 University of Stockholm. All rights reserved.