pod.plot_model_selection

plot_model_selection(cv_scores, used_key=None, cv_winner_key=None)

Generates a normalized bar chart of the Bias-Variance Tradeoff from CV scores, alongside a sorted table of the exact MSE values in best-fit order.

Bars are colour-coded to distinguish the CV winner, the user-forced model (when different from the CV winner), and all other candidates.

Parameters

Name	Type	Description	Default
cv_scores	dict	Dictionary mapping `(model_type, params)` tuples to their Cross-Validation MSE scores.	required
used_key	tuple \| None	The `(type, params)` key of the model that was actually used for the PoD calculation. If `None`, the bar with the lowest MSE is treated as the used model.	`None`
cv_winner_key	tuple \| None	The `(type, params)` key of the CV winner. If `None`, falls back to the bar with the lowest MSE.	`None`

fig = plot_model_selection(
    model.cv_scores_,
    used_key=('Polynomial', 5),
    cv_winner_key=model.cv_winner_
)