COVID-19 Classification Using Machine Learning

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Abstract

COVID-19 is an infectious disorder caused by the SARS-CoV-2 virus, first identified in December 2019. It can cause a range of symptoms such as pneumonia, fatigue, and even death. The study focuses on the COVID-19 dataset, which contains information about patients, symptoms, test results, recovery, and age details. We apply machine learning algorithms, including Random Forest, Decision Trees, KNN, and Naïve Bayes, to predict outcomes of COVID-19, such as test results, recovery time, and hospitalization probability. The dataset undergoes several processing steps, such as handling missing values, normalization, and feature selection. These algorithms are evaluated to determine accuracy, precision, recall, and the confusion matrix to identify the best model.

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