r_precision#

scikitplot.corpus.r_precision(y_true, y_pred, *, sample_weight=None, relevance_threshold=1, duplicates='raise', zero_division='warn', average='mean')[source]#

Precision at |R|, the number of relevant identifiers of each query.

Parameters:
y_truesequence or mapping

Relevance judgments per query.

y_predsequence or mapping

Rankings per query, best first.

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

Per-query weights of the mean.

relevance_thresholdfloat, default=1

Grade from which a judged identifier is relevant.

duplicates{“raise”, “first”}, default=”raise”

What a repeated identifier in a ranking does.

zero_division{“warn”, 0.0, 1.0, np.nan}, default=”warn”

Value for a query without a relevant identifier.

average{“mean”, None}, default=”mean”

None returns the per-query values.

Returns:
float or numpy.ndarray
Parameters:
  • y_true (Any)

  • y_pred (Any)

  • sample_weight (Any)

  • relevance_threshold (float)

  • duplicates (str)

  • zero_division (Any)

  • average (str | None)

Return type:

Any

Examples

>>> r_precision([["a", "b"]], [["a", "x", "b"]])
0.5