Package: recometrics 0.1.6-3

recometrics: Evaluation Metrics for Implicit-Feedback Recommender Systems

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.

Authors:David Cortes

recometrics_0.1.6-3.tar.gz
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recometrics_0.1.6-3.tar.gz(r-4.5-noble)recometrics_0.1.6-3.tar.gz(r-4.4-noble)
recometrics.pdf |recometrics.html
recometrics/json (API)

# Install 'recometrics' in R:
install.packages('recometrics', repos = c('https://david-cortes.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/david-cortes/recometrics/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

implicit-feedbackmatrix-factorizationrecommender-systemsopenblascppopenmp

5.45 score 28 stars 322 downloads 2 exports 6 dependencies

Last updated 2 months agofrom:7fb0244b99. Checks:4 OK, 8 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 13 2025
R-4.5-win-x86_64NOTEMar 13 2025
R-4.5-mac-x86_64NOTEMar 13 2025
R-4.5-mac-aarch64NOTEMar 13 2025
R-4.5-linux-x86_64NOTEMar 13 2025
R-4.4-win-x86_64NOTEMar 13 2025
R-4.4-mac-x86_64NOTEMar 13 2025
R-4.4-mac-aarch64NOTEMar 13 2025
R-4.4-linux-x86_64NOTEMar 13 2025
R-4.3-win-x86_64OKMar 13 2025
R-4.3-mac-x86_64OKMar 13 2025
R-4.3-mac-aarch64OKMar 13 2025

Exports:calc.reco.metricscreate.reco.train.test

Dependencies:floatlatticeMatrixMatrixExtraRcppRhpcBLASctl

Evaluating recommender systems

Rendered fromEvaluating_recommender_systems.Rmdusingknitr::rmarkdownon Mar 13 2025.

Last update: 2021-07-22
Started: 2021-07-12