G1 | R Documentation |
Computes G1 score from a confusion matrix, see confusion. G1 score is F1 score with reversed roles of 0/1 classifications, see Petersen et al. 2022. The G1 score is defined as 2 * TN/(2 * TN + FN + FP), where TN are true negatives, FP are false positives, and FN are false negatives. If TN + FN + FP = 0, 1 is returned.
G1(confusion)
confusion |
Confusion matrix as obtained from confusion |
A numeric in [0,1].
Petersen, Anne Helby, et al. "Causal discovery for observational sciences using supervised machine learning." arXiv preprint arXiv:2202.12813 (2022).
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