lenskit.metrics.Precision#
- class lenskit.metrics.Precision(k=None)#
Bases:
ListMetric
,RankingMetricBase
Compute recommendation precision. This is computed as:
\[\frac{|L \cap I_u^{\mathrm{test}}|}{|L|}\]In the uncommon case that
k
is specified andlen(recs) < k
, this metric useslen(recs)
as the denominator.- Parameters:
k (int | None)
Methods
__init__
([k])measure_list
(recs, test)Compute the metric value for a single result list.
truncate
(items)Truncate an item list if it is longer than
k
.Attributes
default
The default value to infer when computing statistics over missing values.
k
The maximum length of rankings to consider.
The metric's default label in output.
- property label#
The metric’s default label in output.
The base implementation returns the class name by default.