Analysis of Covid-19 (India) Using Machine Learning Algorithms
Author(s):
Prof. S.B. Nikam, Akhil Aditya, Tanish Jain, Yashraj Tandon
Keywords:
COVID, Machine Learning
Abstract
In light of recent events, such as the coronavirus pandemic, prediction algorithms based on machine learning (ML) have proven effective in predicting perioperative outcomes and improving decision-making in the future. Machine learning models have long been used in many application areas that need to detect and prioritize negative threat characteristics. Typically, a variety of forecasting methods are used to address forecasting problems. This study shows how machine learning algorithms can predict the number of patients who will be infected by COVID19, a virus that is now considered a possible threat to humans. In this study, the following predictive model are used to predict COVID19 risk factors: Linear Regression, Exponential Time Smoothing, Autoregressive Integrated Moving Average (ARIMA). The results of the study indicate that these strategies are a viable option in the current COVID19 pandemic.
Article Details
Unique Paper ID: 152525

Publication Volume & Issue: Volume 8, Issue 3

Page(s): 676 - 681
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