Abstract
Early diagnosis is crucial to prevent the development of a disease that may cause danger to human lives. COVID-19, which is a contagious disease that has mutated into several variants, has become a global pandemic that demands to be diagnosed as soon as possible. With the use of technology, available information concerning COVID-19 increases each day, and extracting useful information from massive data can be done through data mining. In this study, authors utilized several supervised machine learning algorithms in building a model to analyze and predict the presence of COVID-19 using the COVID-19 Symptoms and Presence dataset from Kaggle. J48 Decision Tree, Random Forest, Support Vector Machine, K-Nearest Neighbors and Naïve Bayes algorithms were applied through WEKA machine learning software. Each model’s performance was evaluated using 10-fold cross validation and compared according to major accuracy measures, correctly or incorrectly classified instances, kappa, mean absolute error, and time taken to build the model. The results show that Support Vector Machine using Pearson VII universal kernel outweighs other algorithms by attaining 98.81% accuracy and a mean absolute error of 0.012.
Highlights
Coronavirus Disease (COVID-19) is an infectious disease caused by a novel coronavirus that originated in Wuhan China last December (2019)
This study aims to build a model that can automatically predict the presence of COVID-19 in a person utilizing J48 Decision Tree (J48 DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbors (k-NN), and Naïve Bayes (NB) algorithms, by analyzing COVID-19 symptoms using Waikato Environment for Knowledge Analysis (WEKA), which is an open-source software developed at the University of Waikato, New Zealand
This study aims to compare supervised machine learning algorithms to determine which is the most appropriate algorithm to be used in developing a COVID-19 predictor; the optimal performance of an algorithm can be achieved if the best configuration has been utilized in the modeling process
Summary
Coronavirus Disease (COVID-19) is an infectious disease caused by a novel coronavirus that originated in Wuhan China last December (2019). This disease will affect the respiratory system of a person, and some people will eventually get better without having special treatment, especially for those who have a strong immune system [1]. Though, it may be different—old persons are more vulnerable, including those with existing comorbidities such as cardiovascular disease, diabetes, respiratory disease and cancer. COVID-19 can spread because this virus is transmissible by droplets into the air from the infected person through speaking, coughing, and sneezing, or even touching some contaminated objects or areas
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