Department of CSE, Karpagam College of Engineering, Coimbatore, India
Department of CSE, Sri Krishna College of Engineering and Technology, Coimbatore, India
Coronavirus disease, aka COVID-19 is an transmittable disease caused by a newly discovered coronavirus. COVID-19 escalates largely over proximity with a diseased individual at the time of coughing or sneezing. When people touch their nose, eye or mouth, this disease spreads after touching a surface or anything that consists the virus on it. This virus can kill more than 30% of the infected person. Of late, this infectious disease causes the biggest burden on people all over the world. It also has a high death rate. Recently, machine learning based algorithms are being successfully exploited for classifying the data which are successfully adopted in many application areas. Machine learning methods are also can be applied to detect the COVID-19. Feature selection in Machine Learning process plays a significant role in improving the accuracy and other performance aspects. In this work, an approach for prognosing COVID-19 disease recovery is proposed which is realized to be the efficient method. Experimental result show that proposed model outperforms well when compared to other machine learning methods.