论文标题
使用增量allalkmn方法，关于1900案例的数量，印度州的群集改变了印度州的群集
Changing Clusters of Indian States with respect to number of Cases of COVID-19 using incrementalKMN Method
论文作者
论文摘要
印度的新型冠状病毒（Covid-19）的发病率目前正在呈指数升高，但显而易见的生长速率和时间率的空间差异明显变化。我们将各州分为五个群集，低风险类别为高风险类别，并研究不同状态以来如何自$ 30^{th} $ 2020 $ 30^{th} $ 30^{th} $ 2020的$ 30^{th} $自2020年6月的$ 30^{ S.（2019））
The novel Coronavirus (COVID-19) incidence in India is currently experiencing exponential rise but with apparent spatial variation in growth rate and doubling time rate. We classify the states into five clusters with low to the high-risk category and study how the different states moved from one cluster to the other since the onset of the first case on $30^{th}$ January 2020 till the end of unlock 1 that is $30^{th}$ June 2020. We have implemented a new clustering technique called the incrementalKMN (Prasad, R. K., Sarmah, R., Chakraborty, S.(2019))
