mean_average_precision#

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

Mean average precision (MAP), normalised by all relevant identifiers.

Parameters:

y_truesequence or mapping: Relevance judgments per query.
y_predsequence or mapping: Rankings per query, best first.
kint or None, default=None: Cutoff (MAP@k). The normaliser stays |R|, so MAP@k <= recall@k.
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 average precisions.

Returns:

float or numpy.ndarray

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