Pandemia Prediction Using Machine Learning

Coronavirus disease 2019 (COVID-19) is caused a large number of death. Therefore, that Artificial Intelligence (A.I) solution might be capable to identify COVID-19 quickly and early. This paper applies Three ML models to Covid-19 prediction process. We discovered the main dominant variable to decide the negative or positive patient by using different ML models in the prediction process, for instance (LR, XG Boost, and RF). The study and models have been applied for one million patients from European Commission (EC), this data set (cough, fever, sore throat, breath, and headache) been considered as a data sensor coming to the proposed system. The aim is to choose the best ML model for Covid-9 prediction. In addition, all models and dataset have been sufficiently presented with all clarifications and justifications. Also, our data have been provided for one million patients from European Commission (EC). Then, feature selection to prepare the dominant parameters of Cvid-19, which are (cough, fever, sore throat, breath, and headache). As a result, the RF and XG boost obtained the best accuracy in the decision of positive or negative based on nine variables.