measure of agreement F-beta score Philippe Rocca-Serra Shawn Tan The F-beta score is a measure of a model's accuracy, specifically designed to evaluate the performance of binary classification models. It is a generalized form of the F1 score, which itself is the harmonic mean of precision and recall. The F-beta score introduces a way to weigh recall more heavily than precision (or vice versa) depending on the value of beta. adapted from ChatGPT using the following prompt: [what is the F-beta score in statistics] last accessed: July 2024 https://github.com/ISA-tools/stato/pull/86 sklearn.metrics.fbeta_score(y_true, y_pred, *, beta, labels=None, pos_label=1, average='binary', sample_weight=None, zero_division='warn')[source] https://scikit-learn.org/stable/modules/generated/sklearn.metrics.fbeta_score.htm ready for release