Machine Learning Datamining Methods To Predict Fore Coming Covid-19 Cases

Corona virus (CoV) is a broad family of viruses that can cause a variety of illnesses, from the common cold to more serious illnesses. A novel corona virus (nCoV) is a strain of coronavirus that has never been seen in humans before. The disease COVID-19 is caused by SARS-CoV-2, a coronavirus that first appeared in December of 2019. Now, in 2021 we have 4 variants Alpha, Beta, gamma, Delta for which we have no clinically proven vaccines. To stop the rigorousness of the virus the cases have to be predicted so that preventive measures can be implemented in case if higher ratios are depicted. Data mining models were created during this work to discover COVID-19 cases using datasets from covid19india.org. To create the models, the support vector machine, linear regression, polynomial regression, and decision tree techniques were directly implemented on the dataset using the Python programming language. For a given day, the model projected an estimated number of cases. The findings of this study revealed that the model produced using the decision tree data processing algorithm is more efficient in predicting the number of cases with 100% accuracy and it's very simple than any other algorithms.