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')