Detect behavioural anomalies to identify fraudulent users
Final Version.ipynb contains all the updated code
- Encode labels for categorical data -> Assigns numbers to categories
- Extracts more features from dates
- Merge fraudsters data with the transactions they have done to derive a pattern for each transaction
- Since this is one class classification, OneClassSVM is perfect for this situation, derives a pattern for fraud transactions
- Save all the users whose transactions were tagged by the SVM as fraudster