Hello, I am newer to streamlit, please forgive me this is also my first time posting on a technical forum, however this one is driving me crazy.
So created a streamlit app for League of Legends as a capstone for a bootcamp, I am using a MinMaxScaler on collected data from the Riot API, prior to predicting the outcome with a Decision Tree. In my local environment it works flawlessly (after many hours of pulling my hair out). However, once I deployed the code I began getting errors with my MinMaxScaler. This scaler was built and fit in a Jupyter Notebook and saved as a .gz utilizing the joblib package. I load this into my streamlit code utilizing joblib as well. Once my main function runs it throws an error for the scaling function:
AttributeError: 'MinMaxScaler' object has no attribute 'clip' Traceback: File "/usr/local/lib/python3.7/site-packages/streamlit/script_runner.py", line 332, in _run_script exec(code, module.__dict__) File "/app/league_capstone/Streamlit_App.py", line 23, in <module> summoner_data_x, summoner_data_y, summoner_data_raw= full_process(user_input, scaler, games) File "/app/league_capstone/Util.py", line 212, in full_process team_data_x = scale_data(team_data_summoners, scaler, summonerName) File "/app/league_capstone/Util.py", line 200, in scale_data X_num_scaled = scaler.transform(X_num) File "/home/appuser/.local/lib/python3.7/site-packages/sklearn/preprocessing/_data.py", line 439, in transform if self.clip:
What I find strange is that this runs smoothly locally, but once it was deployed there are errors. Any help would be appreciated. I will leave the link to the app, and github repo below.