slickml.visualization._metrics
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Module Contents#
Functions#
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Visualizes binary classification metrics using |
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Visualizes regression metrics using |
- 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 ofBinaryClassificationMetrics
.- 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 ofRegressionMetrics
.- Parameters:
figsize (Tuple[float, float], optional) – Figure size, by default (12, 16)
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