Evaluation Metrics for Implicit-Feedback Recommender Systems
Overview
Calculates evaluation metrics for implicit-feedback recommender systems that are based on low-rank matrix factorization models, given the fitted model matrices and data, thus allowing to compare models from a variety of libraries. Metrics include P@K (precision-at-k, for top-K recommendations), R@K (recall at k), AP@K (average precision at k), NDCG@K (normalized discounted cumulative gain at k), Hit@K (from which the 'Hit Rate' is calculated), RR@K (reciprocal rank at k, from which the 'MRR' or 'mean reciprocal rank' is calculated), ROC-AUC (area under the receiver-operating characteristic curve), and PR-AUC (area under the precision-recall curve). These are calculated on a per-user basis according to the ranking of items induced by the model, using efficient multi-threaded routines. Also provides functions for creating train-test splits for model fitting and evaluation.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘David Cortes <david.cortes.rivera@gmail.com>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: person(given = "David",
family = "Cortes",
role = c("aut", "cre"),
email = "david.cortes.rivera@gmail.com")
as necessary.- NOTE11 OK, 2 NOTENow
- NOTE12 OK, 2 NOTE2026-04-22
- ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
- NOTE12 OK, 2 NOTE2026-04-10
- ERROR12 OK, 1 NOTE, 1 ERROR2026-04-09
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 2
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 50%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- 1
- Median days to close, 50 most recently updated closed PRs
- 0
Checks run against github.com/david-cortes/recometrics on 2026-10-21.
No development-tooling practices detected in the upstream repository.
Dependencies
Installing recometrics adds 4 packages (4 with compiled code, 3.3 MB of source tarballs). Heaviest: Rcpp 1.8 MB, float 1.3 MB, MatrixExtra 208 KB.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.1.6-3Latest
- 0.1.6-12022-08-06 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 0.1.62022-01-20 · diff ↗
- 0.1.5-22021-10-14 · diff ↗
- 0.1.52021-09-02 · diff ↗
- 0.1.32021-07-20 · diff ↗
- 0.1.22021-07-15
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2021-07-15
- Total releases
- 7 / 5 yrs
- License
- BSD_2_clause + file LICENSE OSI
- Download size
- 120 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("recometrics")Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.