def make_predictions(self, hotel_name, platforms): all_reviews = self.read_from_platforms(hotel_name, platforms) reviews_df = self.make_dataframe(all_reviews) nnm = NNModel() predited_df = nnm.generate_predictions(reviews_df) print(predited_df.shape) predited_df.to_csv( 'C:/Users/acfelk/Documents/IIT_Files/final year/FYP/fyp_workfiles/final_project/backend/predicted_data/' + hotel_name + '_' + platforms + '_predicted.csv') return predited_df
def check_predict_ratings(): data = pd.read_csv('test_data/test_revs.csv') nn_model = NNModel() predicted_df = nn_model.generate_predictions(data) predicted_df.to_csv('test_data/predicted_revs.csv') data = pd.read_csv('test_data/predicted_revs.csv') if data['pred_rating'] is not None: print('Testing passed - Reviews Precited Successfully !') os.remove('test_data/predicted_revs.csv') else: print('Review Prediction has failed')