fairlearn.postprocessing.plot_threshold_optimizer#

fairlearn.postprocessing.plot_threshold_optimizer(threshold_optimizer, ax=None, show_plot=True)[source]#

Plot the chosen solution of the threshold optimizer.

For fairlearn.postprocessing.ThresholdOptimizer objects that have their constraint set to ‘demographic_parity’ this will result in a selection/error curve plot. For fairlearn.postprocessing.ThresholdOptimizer objects that have their constraint set to ‘equalized_odds’ this will result in a ROC curve plot.

Parameters:

  • threshold_optimizer (fairlearn.postprocessing.ThresholdOptimizer) – the ThresholdOptimizer instance for which the results should be illustrated.

  • ax (matplotlib.axes.Axes) – a custom matplotlib.axes.Axes object to use for the plots, default None

  • show_plot (bool) – whether or not the generated plot should be shown, default True