- Use of LassoCV to show most important features
- Use of SMOTE to generate synthetic samples during training to tackle unbalanced dataset
- Selection of the most performing algorithm after fine-tuning
- Predictions of the futures flagged clients
The repository comprises :
- A notebook : Scoring_classification.ipynb
- Two CSV files : Training is used to choose and fine-tune the algorithm and the Scoring to predict the class given features