Why 99.83% Accuracy Can Be Misleading: My FraudLens ML Project
Imagine building a fraud detection model that achieves 99.83% accuracy but fails to detect a single fraudulent transaction. That's the problem I wanted to explore with FraudLens ML . The project examines credit-card fraud detection using a benchmark dataset containing 284,807 transactions, includin…
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- 2026-11-09 12:33 · DEV Community — Machine Learning
Why 99.83% Accuracy Can Be Misleading: My FraudLens ML Project