Why Accuracy Misleads and Which Metrics Really Trust Your Models
Relying on raw accuracy can hide a model's real reliability, especially when decisions depend on calibrated probabilities. This piece walks through practical alternatives—calibration curves, Brier score, discrimination metrics—for both classification and regression, showing how they reveal hidden biases and guide safer deployments.