precision_at_k#

scikitplot.corpus.precision_at_k(y_true, y_pred, *, k=10, sample_weight=None, relevance_threshold=1, duplicates='raise', zero_division='warn', average='mean')[source]#

Fraction of the first k ranked identifiers that are relevant.

Parameters:

y_truesequence or mapping: Relevance judgments per query (see _ranking).
y_predsequence or mapping: Rankings per query, best first.
kint or None, default=10: Cutoff. The denominator is k even when fewer are ranked. None divides by the ranking length instead.
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 when the metric is undefined (only without a cutoff, for an empty ranking).
average{“mean”, None}, default=”mean”: None returns the per-query values.

Returns:

float or numpy.ndarray

Raises:

TypeError, ValueError: For malformed inputs; the message names the query.

Parameters:

y_true (Any)
y_pred (Any)
k (int | None)
sample_weight (Any)
relevance_threshold (float)
duplicates (str)
zero_division (Any)
average (str | None)

Return type:

Any