vault / models / gam.md

GAMs & LASSO

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A GAM fits one smooth curve per feature and adds them up - flexible shape, still readable effects; it was my thesis workhorse with leading indicators. LASSO pulls the other lever: keep the model linear and let the penalty push useless coefficients to zero. Reach for a GAM when the curve matters and LASSO when feature count does. Gotcha: smoothness is a hyperparameter - too wiggly and you are fitting noise.

Reference: pyGAM docs.

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