c2v.pl.catboost_perfomance#
- c2v.pl.catboost_perfomance(shapdata, var_names=None, set_type='validation', ncols=4, ax=None, return_fig=False, show=True, figsize=None, line_kws=None, scatter_kws=None, kwargs=None, title=None)#
Compares predicted by CatBoost and observed values. It might help to evaluate performance of CatBoost model.
- Parameters:
- shapdata sc.AnnData
Annotated data matrix.
- var_names str | list[str], optional
Names of the variables to visualize. If None, all fates will be visualized.
- set_type Literal["train", "validation"], optional
Whether to visualize train or validation set.
- ncols int, optional
Number of columns in the plot.
- ax matplotlib.axes.Axes | list[matplotlib.axes.Axes], optional
Axes to plot on. If None, new figure will be created.
- return_fig bool, optional
Whether to return figure object.
- show bool, optional
Whether to show the plot. Default is True.
- figsize tuple[float, float] | None, optional
Figure size. Default is None.
- line_kws dict | list[dict], optional
Keyword arguments for line plot.
- scatter_kws dict | list[dict], optional
Keyword arguments for scatter plot.
- kwargs dict | list[dict], optional
Keyword arguments for sns.lineplot.
- title str | list[str], optional
Title of the plot.
- Return type:
- Returns:
fig : matplotlib.figure.Figure | matplotlib.axes.Axes | np.ndarray | list[matplotlib.axes.Axes] | None Figure object if return_fig is True, Axes if show is False, otherwise None.