Pandemic was present for the entire world from 2019 to 20. Due to this reason the workload for doctors and other healthcare professionals were increased. This workload will be eased by machine learning and the development of computer-aided analytical systems. The goal of the proposed methodology is towards the prevalence of COVID-19 to cost/benefit predictions on real-life dataset. Our proposed methodology is given for weka classification for the accuracy measurement ratios by applying 1R machine learning classifiers Considering the development of clustering with positive and negative occurrences ratios in terms of cost-benefit analysis's initial care projections. In this study 1R Supervised Machine Learning Algorithm have been applied to Covid 19 dataset provided by healthcare organization. The best classification accuracy is obtained from the algorithm of 1R with 75.54%. In this paper visualization Cost/Benefit Analysis and also analysed.

: Visualization,Classification, healthcare, Machine Learning, cost data analysis; decision making; predictions