tabensemb.trainer.Trainer.plot_err_hist

method

Trainer.plot_err_hist(program: str, model_name: str, category: str | None = None, metric: str | None = None, ax=None, legend=True, clr: Iterable | None = None, figure_kwargs: Dict | None = None, hist_kwargs: Dict | None = None, select_by_value_kwargs: Dict | None = None, legend_kwargs: Dict | None = None, savefig_kwargs: Dict | None = None, save_show_close: bool = True) → Axes

Plot histograms of prediction errors.

Parameters:

program

The selected model base.

model_name

The selected model in the model base.

category

The category to classify histograms and stack them with different colors.

metric

The metric to be calculated. It should be supported by tabenseb.utils.utils.auto_metric_sklearn().

ax

matplotlib.axes.Axes

legend

Show legends if category is not None.

clr

A seaborn color palette or an Iterable of colors. For example seaborn.color_palette(“deep”).

figure_kwargs

Arguments for plt.figure.

hist_kwargs

Arguments for ax.hist (used for histograms of continuous features).

select_by_value_kwargs

Arguments for tabensemb.data.datamodule.DataModule.select_by_value().

legend_kwargs

Arguments for plt.legend if legend is True and category is not None.

savefig_kwargs

Arguments for plt.savefig

save_show_close

Whether to save, show (in the notebook), and close the figure if ax is not given.

Returns:

matplotlib.axes.Axes