SelfExplainML / PiML-Toolbox

PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics
https://selfexplainml.github.io/PiML-Toolbox
Apache License 2.0
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Possibly documentation error? #49

Closed Chenchaoyou closed 2 months ago

Chenchaoyou commented 7 months ago

In the user guide 6.6.2.1. Resilience Performance, the description of each figure seems to be wrong.

  1. Worst sample figure: "The curve depicted in the plot is monotonic, indicating that as the worst sample ratio increases, the model’s performance tends to decrease". The figure however seems to be displaying a monotonically increasing AUC as WSR increases.
  2. Outer sample figure: "Interestingly, the model’s performance reaches its peak around the worst sample ratio of approximately 0.7, after which it gradually declines". The figure displays a 0.83 AUC as WSR tends to 1.0.

It could be that I understood it all wrong though. Please let me know if it's an error or that I should understand it all differently. Thank you.

ZebinYang commented 6 months ago

Hi @Chenchaoyou,

Thanks for mentioning that, and the contents in user guide 6.6 were not updated to the example figures.

When the worst-sample ratio is 10%, only the worst-10% samples are selected as "worst samples"; When the worst-sample ratio is 100%, all the test samples are selected as "worst samples". Therefore, the performance is expected to improve as worst-sample ratios increase, which means higher ACC / AUC.