Machine Learning-Based Essentials Covid-19 Symptoms Identification
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Abstract
The major breakdown of Covid-19 was held in the year 2020 around the world. It is the quickest spread disease found in the world. Its symptoms involve cough, temperature, flu, muscle aches, headache, and many others. This study finds the top five clinical symptoms that would lead to COVID-19 in any person and evaluates with supervised learning classifiers: Support Vector Machine (SVM), Gaussian Naïve Bayes, Logistic Regression, K-Nearest Neighbor (KNN), and voting (ensemble) were used. For the evaluation of this, a dataset from Kaggle was selected with 5326 instances and 21 features. Precision, recall, and F-score are the selected performance measures. Different machine-learning classifiers were applied to find the core symptoms of Covid-19. As a result, cough, fever, breathing problems, attending gatherings, and traveling were the prominent symptoms found in this study.
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Pakistan Journal Emerging Science and Technologies (PJEST) in collaboration with Govt. Islamia Graduate College Civil Lines Lahore, Pakistan is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
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