qhjqhj00 matcherrorrate
Metric
MatchErrorRatefromtorchmetrics(torchmetrics.MatchErrorRate)
When to invoke this skill
The user has predictions + ground truth and asks to evaluate with MatchErrorRate, or
mentions torchmetrics.MatchErrorRate directly, or wants the standard torchmetrics implementation.
Reference signature
from torchmetrics import MatchErrorRate
# _MatchErrorRate(**kwargs: Any) -> None
Library docstring
Wrapper for deprecated import.
>>> preds = ["this is the prediction", "there is an other sample"]
>>> target = ["this is the reference", "there is another one"]
>>> mer = _MatchErrorRate()
>>> mer(preds, target)
tensor(0.4444)
Quick recipe
import torchmetrics as _m
score = _m.MatchErrorRate(y_true, y_pred)
Don'ts
- Don't reimplement when the library version handles edge cases (NaN, ties, empty inputs) better than a hand-rolled formula.
- Always check the library version's argument order — sklearn is
(y_true, y_pred)while torchmetrics is(preds, target).