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Feature Engineering That Actually Moves Model Accuracy

Feature engineering is often described as “turning raw data into signals”, but not every engineered feature helps. Some add noise, some duplicate what the...

Fairness Metrics and Demographic Parity Constraints in Model Evaluation

Machine learning models help make decisions in lending, hiring, admissions, and fraud review. Accuracy and AUC matter, but they do not reveal whether outcomes...

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