"A Study on the Development of a Machine Learning Prediction Model on the Spread of COVID-19"
Jaejoon Lee · Biomedical Journal of Scientific & Technical Research · 2022
The corona pandemic has caused many human lives and economic losses.The number of confirmed cases, which slowed since February of this year during the availability of vaccines, increased rapidly due to mutated viruses and casual enforcement of the quarantine system.The difference in this study, as compared to those done previously, is that the most recent data was used, and sufficient learning data is used for training.In addition, the number of confirmed cases was predicted based on the latest information including those who received the primary vaccine and those who were fully vaccinated.In addition, we used a predictive model with information only from confirmed corona cases, subdivided it by parameter, and tried to propose an accurate and effective predictive model for the number of corona-confirmed cases.In this study, the machine-learning model used neural networks, ensembles, distancebased models, and linear regression as supervised learning models.As for the model with excellent predictive power, Gradient Boosting and AdaBoosting had high training scores, and CatBoost showed the best predictive power among the Gradient Boosting models through cross-validation by model.About 94.8% of the predictions were accurate.CatBoost's predictive power was poor in the area where the number of confirmed cases rapidly increased due to the mutated virus.In particular, it was confirmed that the CatBoost model was effective in predicting small and irregular infections in the early stage, but that the prediction of the period of a rapid increase in the number of confirmed cases due to delta mutation was somewhat ineffective.As a future research task, it is necessary to implement and compare prediction algorithms using machine learning techniques trained in unsupervised learning.In addition, it is necessary to make a prediction using the policy variables to be considered, such as the stage and implementation of the social distancing movement.