Regularization and False Alarms Quantification: Two Sides of the Explainability Coin

no code implementations • 2 Dec 2020 • Nima Safaei, Pooria Assadi

Regularization is a well-established technique in machine learning (ML) to achieve an optimal bias-variance trade-off which in turn reduces model complexity and enhances explainability.

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