Monitoring Novel Corona Virus (COVID-19) Infections in India by Cluster Analysis.

It is a great challenge of identification as well as formation of groups of infectious disease data set. Data mining, a process of uncovering silent characteristics of big data is one of such techniques which have nowadays become more popular for treating massive volume of infectious disease data set. In the current study, we apply cluster analysis, one of the data mining techniques to classify real groups of infectious disease "novel corona virus disease (COVID-19)" data set of different states and union territories (UTs) in India according to their high similarity to each other. The results obtained permit us to have a sense of clusters of affected Indian states and UTs. The main objective of clustering in this study is to optimize monitoring techniques in affected states and UTs in India which will be very valuable to the government, doctors, the police and others involved in understanding seriousness of the spread of novel coronavirus (COVID-19) to improve government policies, decisions, medical facilities (ventilators, testing kits, masks etc.), treatment etc. to reduce number of infected and deceased persons.