Build an Imbalanced Fraud Classifier with SMOTE and Cost-Sensitive Learning Free

Catch card-not-present fraud at a 0.17% base rate by combining cost-sensitive gradient boosting with SMOTE, lifting PR-AUC from 0.124 to 0.612 and cutting net fraud loss 42% inside a 40ms scoring budget.