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recometrics  

Evaluation Metrics for Implicit-Feedback Recommender Systems
View on CRAN: Click here


Download and install recometrics package within the R console
Install from CRAN:
install.packages("recometrics")

Install from Github:
library("remotes")
install_github("cran/recometrics")

Install by package version:
library("remotes")
install_version("recometrics", "0.1.6-3")



Attach the package and use:
library("recometrics")
Maintained by
David Cortes
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-07-15
Latest Update: 2023-02-19
Description:
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.
How to cite:
David Cortes (2021). recometrics: Evaluation Metrics for Implicit-Feedback Recommender Systems. R package version 0.1.6-3, https://cran.r-project.org/web/packages/recometrics
Previous versions and publish date:
0.1.2 (2021-07-15 13:10), 0.1.3 (2021-07-20 09:40), 0.1.5-2 (2021-10-14 06:30), 0.1.5 (2021-09-02 19:20), 0.1.6-1 (2022-08-06 21:40), 0.1.6 (2022-01-20 23:52)
Other packages that cited recometrics R package
View recometrics citation profile
Other R packages that recometrics depends, imports, suggests or enhances
Functions, R codes and Examples using the recometrics R package
Some associated functions: calc.reco.metrics . create.reco.train.test . 
Some associated R codes: RcppExports.R . recometrics.R .  Full recometrics package functions and examples
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