def main():
#os.chdir('../') # Set working directory
print("\nStarting program.\n")
print("Loading data...\n")
accidents_data = ld.AccidentsData()
vehicles_data = ld.VehiclesData()
merged_data = ld.MergedData(accidents_data, vehicles_data)
X_test = merged_data.get_merged_test()
y_test = merged_data.get_target_test()
X_train = merged_data.get_merged_train()
y_train = merged_data.get_target_train()
print("Available Models:\n")
print("1. K-nearest Neighbors")
print("2. Stochastic Gradient Descent Classifier")
print("3. Decision Tree Classifier")
print("4. Random Forest Classifier")
print("5. C-Support Vector Classification")
print("6. Logistic Regression")
print("7. Multi-Layer Perceptron Classifier")
print("\n")
mode = input("Choose Training Model: ")
print('\nTraining model...\n')
training = tr.Training(X_train, y_train)
if mode == "1":
training.knnTraining()
elif mode == "2":
training.sgdClassifierTraining()
elif mode == "3":
training.decisionTreeTraining()
elif mode == "4":
training.supportVectorMachinesTraining()
elif mode == "5":
training.supportVectorMachinesTraining()
elif mode == "6":
training.logisticRegressionTraining()
elif mode == "7":
training.mlpTraining()
else:
print("Bye!")
quit()
print('Calculating prediction...')
y_pred = training.model.predict(X_test.drop('accident_id', axis=1))
print('F1 score = ', f1_score(y_test,y_pred))
