src.plot.advanced_classification_plot
Classes
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- class src.plot.advanced_classification_plot.AdvancedClassificationPlot(**kwargs)
- Author:
Alberto M. Esmoris Pena
Class to plot the advanced evaluation of a classification task.
See
MplPlotandAdvancedClassificationEvaluation.- Variables:
evals (list of
ClassificationEvaluation) – The many evaluations on the classification based on the requested filters.class_names (list of str) – The names for each class involved in the classification.
domain_name – See
AdvancedClassificationEvaluator.num_points – See
AdvancedClassificationEvaluation.num_fpoints – See
AdvancedClassificationEvaluation.
- __init__(**kwargs)
Initialize an instance of AdvancedClassificationPlot.
- Parameters:
kwargs – The key-word arguments defining the plot’s attributes.
- plot(**kwargs)
Plot the global metrics, class-wise metrics, confusion matrices, and class distributions if the information is available.
See
plot.Plot.plot().
- plot_global_metrics(**kwargs)
Plot the global metrics.
- plot_classwise_metrics(**kwargs)
Plot the class-wise metrics.
- plot_confusion_matrices(**kwargs)
Plot the confusion matrices.
- plot_class_distribution(**kwargs)
Plot the class distribution for each node in the domain.
- has_global_metrics()
Check whether the plot contains global metrics.
- Returns:
True if the plot contains global metrics, False otherwise.
- has_classwise_metrics()
Check whether the plot contains class-wise metrics.
- Returns:
True if the plot contains class-wise metrics, False otherwise.
- has_confusion_matrices()
Check whether the plot contains confusion matrices.
- Returns:
True if the plot contains confusion matrices, False otherwise.
- has_class_distribution()
Check whether the plot contains all the information needed to plot the class distribution.
- Returns:
True if the plot contains all the information needed to plot the class distribution.