Enabling Healthcare 4.0 for Pandemics

3Analysis and Prediction on COVID-19 Using Machine Learning Techniques

Supriya Raheja^* and Shaswata Datta

Department of CSE, Amity University, Noida, India

Abstract

This paper presents an analysis and prediction of COVID-19 data using machine learning techniques. The present work discusses different machine learning techniques namely linear regression, logistic regression, random forest, and decision tree. The outbreak COVID-19 has attracted the attention of all researchers only on the corona virus. To focus on COVID-19, the present study attempts to analyze COVID-19 data using all machine learning techniques. The work also introduced a decision-making process for further prediction. The techniques are compared with respect to accuracy of prediction.

Keywords: COVID-19, data analysis, linear regression, logistic regression, random forest, decision tree, prediction

3.1 Introduction

These days, lots of data are generated due to tremendous use of internet worldwide which is useless without finding the hidden insights of the data. These findings can be used by organizations for their various future decisions making. As reviewed from literature, web has all the documents present in it and its volume is increasing in gargantuan rate of about 80% per year [1]. Moreover, almost all the data are stored in text format in websites in unstructured form. With a very powerful tool like machine learning, it becomes very easy to operate these enormous amounts of data and find data prediction ...