RF-COVID-19-SE-USA

Project that uses Random Forest Regression to forecast the number of COVID-19 infections and deaths in the Southeastern United States

SouthEast Counties:

SouthEast_Counties.csv: dataset that contains states and counties names (used for reference)

SE_Counties.csv: dataset used for Tests 1 and 2

Cases

• SE_Cases.py: Program for Test 1 Case 1 (predicts number of cases)

• results_cases.csv: Test 1 Case 1 results

Cases (Deaths Removed)

• SE_Cases_Deaths_Removed.py: Program for Test 1 Case 2 (predicts number of cases)

• results_cases_deaths_removed.csv: Test 1 Case 2 results

Cases (Area and Population Density Removed)

• SE_Cases_A&PD_Removed.py: Program for Test 1 Case 3 (predicts number of cases)

• results_cases_a&pd_removed.csv: Test 1 Case 3 results

Cases (Population Density Removed)

• SE_Cases_PD_Removed.py: Program to predict number of cases without using population density (not in report)

• results_cases_pd_removed.csv: results for above program

Cases (Area Removed)

• SE_Cases_Area_Removed.py: Program to predict number of cases without using area (not in report)

• results_cases_area_removed.csv: results for above program

Cases (Area and Population Removed)

• SE_Cases_A&P_Removed.py: Program to predict number of cases without using area or population (not in report)

• results_cases_a&P_removed.csv: results for above program

Deaths

• SE_Deaths.py: Program for Test 2 Case 1 (predicts number of deaths)

• results_deaths.csv: Test 2 Case 1 results

• results_deaths_accuracy.csv: Test 2 Case 1 results with calculated accuracies

Deaths (Cases Removed)

• SE_Deaths_Cases_Removes.py: Program for Test 2 Case 2 (predicts number of deaths)

• results_deaths_cases_removed.csv: Test 2 Case 2 results

• results_deaths_cases_removed_accuracy.csv: Test 2 Case 2 results with calculated accuracies

Deaths (Area and Population Density Removed)

• SE_Deaths_A&PD_Removes.py: Program for Test 2 Case 3 (predicts number of deaths)

• results_a&pd_cases_removed.csv: Test 2 Case 3 results

• results_a&pd_cases_removed_accuracy.csv: Test 2 Case 3 results with calculated accuracies

SouthEast States:

SE_States.csv: dataset used for Tests 3 and 4

Total Cases

• States_Cases.py: Program for Test 3 Case 1 (predicts number of total cases)

• results_tot_cases.csv: Test 3 Case 1 results

Total Cases (Total Deaths Removed)

• States_Cases_TD_Removed.py: Program for Test 3 Case 2 (predicts number of total cases)

• results_tot_cases_td_removed.csv: Test 3 Case 2 results

Total Cases (Optimized)

• States_Cases_Optimized.py: Program for Test 3 Case 3 (predicts number of total cases)

• results_tot_cases_optimized.csv: Test 3 Case 3 results

Total Death

• States_Death.py: Program for Test 4 Case 1 (predicts number of total deaths)

• results_tot_death.csv: Test 4 Case 1 results

• results_tot_death_accuracy.csv: Test 4 Case 1 results with calculated accuracies

Total Death (Total Cases Removed)

• States_Death_TC_Removed.py: Program for Test 4 Case 2 (predicts number of total deaths)

• results_tot_death_tc_removed.csv: Test 4 Case 2 results

• results_tot_death_tc_removed_accuracy.csv: Test 4 Case 2 results with calculated accuracies

Total Death (Optimized)

• States_Death_Optimized.py: Program for Test 4 Case 3 (predicts number of total cases)

• results_tot_death_optimized.csv: Test 4 Case 3 results

• results_tot_death_optimzed_accuracy.csv: Test 4 Case 3 results with calculated accuracies

New Cases

• States_New_Cases.csv: Program to predict the baseline number of new cases (not in report)

• results_new_cases.csv: Results for above program

• results_new_cases_accuracy.csv: Results for above program with calculated accuracies

New Cases (Optimized)

• States_New_Cases_Optimized.csv: Program to predict the attempted optimization of number of new cases (not in report)

• results_new_cases_optimized.csv: Results for above program

• results_new_cases_optimized_accuracy.csv: Results for above program with calculated accuracies