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📚TheoryIntermediate

Double Descent Phenomenon

Double descent describes how test error first follows the classic U-shape with increasing model complexity, spikes near the interpolation threshold, and then drops again in the highly overparameterized regime.

#double descent#interpolation threshold#overparameterization+12
📚TheoryAdvanced

Statistical Learning Theory

Statistical learning theory explains why a model that fits training data can still predict well on unseen data by relating true risk to empirical risk plus a complexity term.

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Filtering by:
#bias variance tradeoff
#statistical learning theory
#empirical risk minimization
#structural risk minimization
+11
📚TheoryIntermediate

Bias-Variance Tradeoff

The bias–variance tradeoff explains how prediction error splits into bias squared, variance, and irreducible noise for squared loss.

#bias variance tradeoff#mse decomposition#polynomial regression+12