3.4. Machine Learning Models
In line with the objectives of the study, classifiers were built based
on a set of independent variables to predict if any country that has
COVID-19 infections shows early signs of infection containment as a
reflection of policy implementations and behaviour changes. Logistic
regression was used to understand the list of independent variables
significantly affecting the infection containment and their
corresponding importance in the model. Then, to predict signs of early
containment, machine learning algorithms like logistic regression,
decision trees, random forest and support vector machines were used and
their corresponding accuracies are compared. For all models,
cross-validation was done in 5 folds to address overfitting.