An Ensemble Feature Selection Approach-Based Machine Learning Classifiers for Prediction of COVID-19 Disease

Table 1

Features extracted using different feature selection methods.

Feature selection methods	Israeli COVID-19 dataset	Symptoms and COVID-19 presence dataset
Chi-square	1. Cough; 2. Fever; 3. Sore throat; 4. Headache; 5. Test indication	1. Breathing problem; 2. Fever; 3. Dry cough; 4. Sore throat; 5. Abroad travel; 6. Contact with COVID-19 patient; 7. Attended large gathering
RFE	1. Cough; 2. Sore throat; 3. Headache; 4. Age of 60 years and above; 5. Test indication	1. Breathing problem; 2. Fever; 3. Dry cough; 4. Sore throat; 5. Abroad travel; 6. Contact with COVID-19 patient; 7. Attended large gathering
GA	1. Cough; 2. Sore throat; 3. Headache	1. Breathing problem; 2. Sore throat; 3. Asthma; 4. Chronic lung disease; 5. Abroad travel; 6. Contact with COVID-19 patient; 7. Wearing masks
PSO	1. Cough; 2. Fever; 3. Sore throat; 4. Shortness of breath; 5. Gender	1. Breathing problem; 2. Fever; 3. Dry cough; 4. Sore throat; 5. Running nose; 6. Abroad travel; 7. Visited public exposed places
Random forest	1. Cough; 2. Fever; 3. Sore throat; 4. Headache; 5. Test indication	1. Breathing problem; 2. Fever; 3. Dry cough; 4. Sore throat; 5. Abroad travel; 6. Contact with COVID-19 patient; 7. Attended large gathering