AnkurSingh23/Credit_Card_Fraud_Detection

A notebook-based case study on detecting fraudulent transactions using ML on a highly imbalanced dataset (~0.17% fraud). Performed EDA, preprocessing (scaling, stratified split, leakage prevention), and compared Logistic Regression vs Random Forest. Focused on recall, precision, and ROC-AUC to build a reliable fraud detection pipeline.

语言：Jupyter Notebook · GitHub 星标：4 · Fork：0

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