A free Python app lets users manipulate simulated class distributions and the threshold to see how classification metrics such as ROC AUC, MCC, and F1 change together.
A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis,
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Interactive Classification Metrics: A graphical application to build robust intuition for classification model evaluation
A free Python app lets users manipulate simulated class distributions and the threshold to see how classification metrics such as ROC AUC, MCC, and F1 change together.