edit_similarity_score#

scikitplot.corpus.edit_similarity_score(y_true, y_pred, *, normalize=None, backend='auto', sample_weight=None, average='mean')[source]#

Mean normalised edit similarity between predictions and references.

Parameters:
y_truesequence or mapping

Reference answers per item: a str or a sequence of str.

y_predsequence or mapping

Predicted answer per item (str), aligned with y_true.

normalize{None, “basic”, “squad”}, default=None

Normalisation of both sides.

backend{“auto”, “python”}, default=”auto”

Edit-distance implementation (both exact).

sample_weightarray-like of shape (n_items,), default=None

Per-item weights of the mean.

average{“mean”, None}, default=”mean”

None returns per-item values.

Returns:
float or numpy.ndarray
Parameters:

  • y_true (Any)

  • y_pred (Any)

  • normalize (str | None)

  • backend (str)

  • sample_weight (Any)

  • average (str | None)

Return type:

Any

See also

edit_similarity, anls_score

Examples

>>> edit_similarity_score(["kitten"], ["sitting"])
0.5714285714285714