edaflow.ml.plot_learning_curvesο
- edaflow.ml.plot_learning_curves(model: BaseEstimator, X_train: DataFrame, y_train: Series, cv: int = 5, scoring: str = 'auto', train_sizes: ndarray | None = None, title: str | None = None, figsize: Tuple[int, int] = (10, 6), show_std: bool = True) Figure[source]ο
Plot learning curves to analyze model performance vs training set size.
Parameters:ο
- modelBaseEstimator
The model to analyze
- X_trainpd.DataFrame
Training features
- y_trainpd.Series
Training target
- cvint, default=5
Number of cross-validation folds
- scoringstr, default=βautoβ
Scoring metric
- train_sizesnp.ndarray, optional
Training set sizes to use
- titlestr, optional
Plot title
- figsizeTuple[int, int], default=(10, 6)
Figure size
- show_stdbool, default=True
Whether to show standard deviation bands
Returns:ο
- plt.Figure
The matplotlib figure