More on Covid -19 Using Machine Learning

astha pathak, Rita Sahani

Abstract


Covid sickness (COVID-19) is an aggravation illness from another infection. The sickness causes respiratory infirmity (like flu) with indications, for instance, cool, hack and fever, and in continuously genuine cases, the issue in relaxing. Coronavirus 2019 has been seen as an overall pandemic and a couple of assessments are being driven using diverse mathematical models to foresee the reasonable headway of this disease. These mathematical models reliant on various components and examinations are needy upon expected tendency. Here, we introduced a model that could be helpful to foresee the spread of COVID-2019. We have performed straight relapse, Multilayer perceptron and Vector autoregression strategy for want on the COVID-19 Kaggle information to foresee the epidemiological case of the affliction and movement of COVID-2019 across the world. Best models accomplished comprises of 4 concealed layers with 4 neurons in every one of those layers, and utilize a ReLU actuation work, with R2 scores of 0.98599 for confirmed, 0.99429 for expired, and 0.97941 for recuperated understanding models. At the point when cross-approval is played out, these scores drop to 0.94 for confirmed, 0.781 for recuperated, and 0.986 for expired patient models, indicating high vigor of the perished persistent model, great heartiness for confirmed, and low power for recuperated tolerant model.


Keywords


COVID-19 ,Prediction • Linear regression (LR), kaggle

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