The aim of this project is to recognize spam users among Decidim.
A decision tree classifier has been trained to assign a probability to every user of a decidim database.
- Python >= 3.8
- pip >= 21.x.x
This project can be executed only by decidim admins, the data has to be passed by the HTTP method: request
To deploy this project run:
pip install -r requiremts.txt
python app.py- Put a csv inside the data folder with the following columns:
'sign_in_count', 'personal_url', 'about', 'avatar', 'extended_data', 'followers_count', 'following_count', 'invitations_count', 'failed_attempts', 'admin', 'is_spam'
You can use
train_example.csvas example. make train- Move new_model.pkl and replace model.pkl in the main folder.