A Novel Algorithm for Data Centric Perspective Analysis on the Covid-19 Crisis

The sudden arise of novel corona virus in wuhan, china spread in a brief span of time, everywhere across the world. unfortunately, India is the second most affected country after united states with the case count of 33,971,607 and death count about 450,814.Sudden spread of covid -19 in India hit the indian economy strongly and leads to increased number of death when compared to others severe disease like severe Acute Respiratory Syndrome(SARS)and Spanish flu etc.., Collection of data about recovered cases, confirmed cases and confirmed death helps government of india and health care workers to take prevention measures to control the pandemic situation. In this paper, a novel regression model has been introduced to predict with better accuracy the COVID cases. The goal of this research is to do a data centric perspective analysis on the various methods, such as decision trees, LSTMs, RNN and CNN algorithms to tackle the Corona virus outbreak. The collection includes information on positive samples, confirmed fatalities, and retrieved cases of the Covid-19 epidemic in India. With respect to the time period, three – fourth of the data is used as a training dataset and the remaining one – fourth as a test dataset. It not only analyses datasets effectively utilizing regression techniques such as LSTM, CNN, and DT, but it also calculates the r2 score at the end of the execution in Python notebook.