SRM: Regularisation trades fit for stability
A penalty changes the coefficient estimation problem. Ridge shrinks coefficients using a squared penalty; lasso can set some coefficients to zero. Compare models on a consistent scale, because predictor units affect penalised estimation.
Worked example or practice scenario
A predictor measured in dollars and another measured in thousands of dollars encode the same information but have different coefficient magnitudes. Penalising raw coefficients without accounting for scale can treat the two versions differently. Standardisation can make the intended penalty comparison clearer.
Try this next
Standardise using training-set means and scales, then tune the penalty with an appropriate validation scheme. Record whether the intercept is penalised. Distinguish selecting a useful predictive model from claiming that every selected variable has a causal effect.
Reading sources
ActNet editorial guide · October 1, 2026 · Original illustrative examples.