`slickml.visualization._metrics`#

Module Contents#

Functions#

`plot_binary_classification_metrics`(, save_path, ...)	Visualizes binary classification metrics using `plotting_dict_` attribute of `BinaryClassificationMetrics`.
`plot_regression_metrics`(, save_path, display_plot, ...)	Visualizes regression metrics using `plotting_dict_` attribute of `RegressionMetrics`.

slickml.visualization._metrics.plot_binary_classification_metrics(figsize: Optional[Tuple[float, float]] = (12, 12), save_path: Optional[str] = None, display_plot: Optional[bool] = False, return_fig: Optional[bool] = False, **kwargs: Dict[str, Any]) → Optional[matplotlib.figure.Figure][source]#

Visualizes binary classification metrics using plotting_dict_ attribute of BinaryClassificationMetrics.

Parameters:

figsize (Tuple[float, float], optional) – Figure size, by default (12, 12)
save_path (str, optional) – The full or relative path to save the plot including the image format such as “myplot.png” or “../../myplot.pdf”, by default None
display_plot (bool, optional) – Whether to show the plot, by default False
return_fig (bool, optional) – Whether to return figure object, by default False
**kwargs (Dict[str, Any]) – Key-value pairs of regression metrics plot

Returns:

Figure, optional

slickml.visualization._metrics.plot_regression_metrics(figsize: Optional[Tuple[float, float]] = (12, 16), save_path: Optional[str] = None, display_plot: Optional[bool] = False, return_fig: Optional[bool] = False, **kwargs: Dict[str, Any]) → matplotlib.figure.Figure[source]#

Visualizes regression metrics using plotting_dict_ attribute of RegressionMetrics.