lenskit.metrics.ranking.Precision#

class lenskit.metrics.ranking.Precision(n=None, *, k=None)#

Bases: lenskit.metrics.ranking._base.ListMetric, lenskit.metrics.ranking._base.RankingMetricBase

Compute recommendation precision. This is computed as:

\[\frac{|L \cap I_u^{\mathrm{test}}|}{|L|}\]

In the uncommon case that k is specified and len(recs) < k, this metric uses len(recs) as the denominator.

Stability:
Caller (see Stability Levels).
Parameters:

  • n (int | None)

  • k (int | None)

property label#

The metric’s default label in output. The base implementation returns the class name by default.

measure_list(recs, test)#

Compute measurements for a single list.

Returns:

  • A float for simple metrics

  • Intermediate data for decomposed metrics

  • A dict mapping metric names to values for multi-metric classes

Parameters:
Return type:

float