Analysis and Prediction of COVID-19 using Regression Models and Time Series Forecasting
Proc. Conflu.: Int. Conf. Cloud Comput., Data Sci. Eng.
; : 989-995, 2021.
Article
in English
| Scopus | ID: covidwho-1186092
ABSTRACT
In this paper, we are predicting and forecasting the COVID-19 outbreak in India based on the machine learning approach, where we aim to determine the optimal regression model for an in-depth analysis of the novel Coronavirus in India. We are implementing the two regression models namely linear and polynomial and evaluating the two using the R squared score and error values. The COVID-19 dataset for India is being used to serve the research of this paper. The model is predicting the number of confirmed, recovered, and death cases based on the data available from March 12 to October 31,2020. For forecasting the future trend of these cases, we are utilizing the time series forecasting approach of tableau. Furthermore, the time series forecasting method is being employed to forecast the total count of confirmed cases in the future. © 2021 IEEE
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
/
Prognostic study
Language:
English
Journal:
Proc. Conflu.: Int. Conf. Cloud Comput., Data Sci. Eng.
Year:
2021
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS