About this document
Credit Card Fraud Detection Model Insights by Pulkit Dubey is a document available to read on EtoBox.
The project focused on building a machine learning model to detect fraudulent credit card transactions using a dataset of 1,000 entries. Data preprocessing involved one-hot and frequency encoding, as well as addressing class imbalance with SMOTE. The Random Forest model achieved the best F1-score of ~0.28, and the project highlighted challenges with data imbalance and the importance of careful data cleaning and encoding.
- Author
- Pulkit Dubey
- Language
- EN