edaflow.ml.plot_validation_curves

edaflow.ml.plot_validation_curves(model: BaseEstimator, X_train: DataFrame, y_train: Series, param_name: str, param_range: List[Any], cv: int = 5, scoring: str = 'auto', title: str | None = None, figsize: Tuple[int, int] = (10, 6), log_scale: bool = False) → Figure

Plot validation curves for hyperparameter analysis.

Parameters:

modelBaseEstimator

The model to analyze

X_trainpd.DataFrame

Training features

y_trainpd.Series

Training target

param_namestr

Name of the parameter to vary

param_rangeList[Any]

Range of parameter values to test

cvint, default=5

Number of cross-validation folds

scoringstr, default=’auto’

Scoring metric

titlestr, optional

Plot title

figsizeTuple[int, int], default=(10, 6)

Figure size

log_scalebool, default=False

Whether to use log scale for x-axis

Returns:

plt.Figure

The matplotlib figure