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:
recometrics_0.1.6-3.tar.gz
recometrics_0.1.6-3.zip(r-4.5)recometrics_0.1.6-3.zip(r-4.4)recometrics_0.1.6-3.zip(r-4.3)
recometrics_0.1.6-3.tgz(r-4.5-x86_64)recometrics_0.1.6-3.tgz(r-4.5-arm64)recometrics_0.1.6-3.tgz(r-4.4-x86_64)recometrics_0.1.6-3.tgz(r-4.4-arm64)recometrics_0.1.6-3.tgz(r-4.3-x86_64)recometrics_0.1.6-3.tgz(r-4.3-arm64)
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
implicit-feedbackmatrix-factorizationrecommender-systemsopenblascppopenmp
Last updated 2 months agofrom:7fb0244b99. Checks:4 OK, 8 NOTE. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 13 2025 |
R-4.5-win-x86_64 | NOTE | Mar 13 2025 |
R-4.5-mac-x86_64 | NOTE | Mar 13 2025 |
R-4.5-mac-aarch64 | NOTE | Mar 13 2025 |
R-4.5-linux-x86_64 | NOTE | Mar 13 2025 |
R-4.4-win-x86_64 | NOTE | Mar 13 2025 |
R-4.4-mac-x86_64 | NOTE | Mar 13 2025 |
R-4.4-mac-aarch64 | NOTE | Mar 13 2025 |
R-4.4-linux-x86_64 | NOTE | Mar 13 2025 |
R-4.3-win-x86_64 | OK | Mar 13 2025 |
R-4.3-mac-x86_64 | OK | Mar 13 2025 |
R-4.3-mac-aarch64 | OK | Mar 13 2025 |
Exports:calc.reco.metricscreate.reco.train.test
Dependencies:floatlatticeMatrixMatrixExtraRcppRhpcBLASctl
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Calculate Recommendation Quality Metrics | calc.reco.metrics |
Create Train-Test Splits of Implicit-Feedback Data | create.reco.train.test |