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))