def train_and_get_metrics(): print('LOADING DATA') # Load Data data = LoadData(x_input_features=[5, 6, 7]) data.load_processed_data() train_data = data.load_train_data() validation_data = data.load_validation_data() test_data = data.load_test_data() print('TRAINING CLASSIFIER') # Run Model transaction_classifier = TransactionClassifier() transaction_classifier.train(train_data) print('TESTING CLASSIFIER') train_results = transaction_classifier.test(train_data) val_results = transaction_classifier.test(validation_data) test_results = transaction_classifier.test(test_data) print('STATS:') print('------------ TRAIN SET -------------') print('LENGTH =', len(train_data[0])) print('Metrics:\n', train_results) print('------------ VALIDATION SET -------------') print('LENGTH =', len(validation_data[0])) print('Metrics:\n', val_results) print('------------ TEST SET -------------') print('LENGTH =', len(test_data[0])) print('Metrics:\n', test_results) print('++++++++++++++++++++++++++++++++++++++++') print('SAVING CLASSIFIER') transaction_classifier.save_model()