A Comparative Analysis of Different Regression Models on Predicting the Spread of Covid-19 in India

Abstract

According to the World Health Organization (WHO) Situation Reports of Corona Virus Disease(Covid-19), as on 15 th May 2020, India has 81,970 totals confirmed cases, 2649 total deaths and is still within the limit of community transmission phase. In this study, we analyze the spread of the disease and the fatalities caused up to 15 th May 2020, as per the data obtained. A granular computing based regression model, namely Granular Box Regression is used along with Linear Regression for comparative analysis to study the increase in the number of confirmed cases and deaths based on days and an increase in the number of samples tested per day. A separate analysis is also conducted to evaluate the performance of Polynomial Regression on the same dataset. The performance of the different models has been evaluated using R-squared, Mean Absolute Error, Root Mean Squared Error, and Mean Squared Error values.

Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review

“…In [59] Chakraborty et al proposed to use Linear Regression, Polynomial Regression and a granular computing based regression model, the Granular Box Regression (GBR), to predict the daily increase of new COVID-19 cases in India. GBR finds the relationship between independent variables and a dependent variable by using multidimensional boxes.…”

Forecasting COVID-19 Cases in Algeria using Logistic Growth and Polynomial Regression Models

“…In the same way, Chakraborty et al [29] compared the performance of the linear regression model, granular box regression, and the polynomial regression model in predicting the spread of COVID-19 in India. The authors reported that the polynomial regression model outperformed the two other models.…”

Forecasting COVID-19 cases in Algeria using logistic growth and polynomial regression models

“…In the same way Chakraborty et al, 2020 [29] compared the performance between Linear Regression model, Granular Box Regression (GBR) and the Polynomial Regression model in predicting the spread of COVID-19 in India. The authors reported that the Polynomial regression model surpassed the two other models.…”