Analyzing COVID-19 patients of different Region in Philipen Using K-Means Clustering Algorithm

Abstract

This paper present unsupervised learning K-mean clustering for the cataloguing of COVID-19 patients in philipen. The dataset for the present analysis retrieved from )KCDC( can be obtain COVID-19 dataset from website (Kagge). K-means clustering is applied for the 5000 instances based on five attribute ( Gender,Age-group,Health state,Region,Case-id) This work exhibits performance of the unsupervised learning technique by  This paper that very importance, when see the differences among attributes for cases of virus infection and total deaths and . correct use of these dataset will help peoples in different region in Philipen take precautions regarding virus.