[scikit-learn] random forests and multil-class probability

[Matteo Caorsi]

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On 27 Jul 2021, at 12:42, Brown J.B. via scikit-learn <scikit-learn at python.org> wrote:

2021年7月27日(火) 12:03 Guillaume Lemaître <g.lemaitre58 at gmail.com>:
As far that I remember, `precision_recall_curve` and `roc_curve` do not support multi class. They are design to work only with binary classification.

Correct, the TPR-FPR curve (ROC) was originally intended for tuning a free parameter, in signal detection, and is a binary-type metric.
For ML problems, it lets you tune/determine an estimator's output value threshold (e.g., a probability or a raw discriminant value such as in SVM) for arriving an optimized model that will be used to give a final, binary-discretized answer in new prediction tasks.

Hope this helps, J.B.

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