Package: recommenderlab 1.1.0

recommenderlab: Lab for Developing and Testing Recommender Algorithms

Provides a research infrastructure to develop and evaluate collaborative filtering recommender algorithms. This includes a sparse representation for user-item matrices, many popular algorithms, top-N recommendations, and cross-validation. Hahsler (2022) <doi:10.48550/arXiv.2205.12371>.

Authors:Michael Hahsler [aut, cre, cph], Bregt Vereet [ctb]

recommenderlab_1.1.0.tar.gz
recommenderlab_1.1.0.zip(r-4.7-any)recommenderlab_1.1.0.zip(r-4.6-any)recommenderlab_1.1.0.zip(r-4.5-any)
recommenderlab_1.1.0.tgz(r-4.6-any)recommenderlab_1.1.0.tgz(r-4.5-any)
recommenderlab_1.1.0.tar.gz(r-4.7-any)recommenderlab_1.1.0.tar.gz(r-4.6-any)
recommenderlab_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
recommenderlab/json (API)

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

Bug tracker:https://github.com/mhahsler/recommenderlab/issues

Pkgdown/docs site:https://michael.hahsler.net

Datasets:

On CRAN:

Conda:

collaborative-filteringrecommender-system

11.10 score 216 stars 3 packages 1.1k scripts 2.1k downloads 1 mentions 49 exports 7 dependencies

Last updated from:37ebf8d0ba. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK173
source / vignettesOK260
linux-releaseOK185
macos-releaseOK169
macos-oldrelOK115
windows-develOK141
windows-releaseOK110
windows-oldrelOK111
wasm-releaseOK88

Exports:avgbestNbinarizecalcPredictionAccuracycoercecolCountscolSdsdenormalizedissimilaritydropNAdropNA2matrixdropNAis.naevaluateevaluationSchemefrobeniusfunkSVDgetConfusionMatrixgetDatagetData.framegetListgetModelgetNormalizegetParametersgetRatingMatrixgetRatingsgetResultsgetRunsgetTopNListshasRatingHybridRecommenderimageMAEMSEnormalizenratingsplotpredictRecommenderrecommenderRegistryremoveKnownItemsremoveKnownRatingsreturnRatingsRMSErowCountsrowSdssampleshowsimilaritysummary

Dependencies:arulesgenericslatticeMatrixmatrixStatsproxyregistry

An introduction to the R package recommenderlab
Introduction | Collaborative Filtering | Evaluation of Recommender Algorithms | Recommenderlab Infrastructure | Examples | Conclusion
Rendered fromrecommenderlab_vignette.Rnwusingutils::Sweave

Last update: 2026-10-05
Started: 2026-09-27

Getting started with recommenderlab
Installation | Load and prepare ratings | Fit a recommender and make recommendations | Evaluate recommendations | Where to go next
Rendered fromrecommenderlab.Rmdusingknitr::rmarkdown

Last update: 2026-10-01
Started: 2026-09-27

Readme and manuals

Help Manual

Help pageTopics
Class "binaryRatingMatrix": A Binary Rating MatrixbinaryRatingMatrix binaryRatingMatrix-class coerce,binaryRatingMatrix,dgCMatrix-method coerce,binaryRatingMatrix,dgTMatrix-method coerce,binaryRatingMatrix,itemMatrix-method coerce,binaryRatingMatrix,list-method coerce,binaryRatingMatrix,matrix-method coerce,binaryRatingMatrix,ngCMatrix-method coerce,data.frame,binaryRatingMatrix-method coerce,itemMatrix,binaryRatingMatrix-method coerce,matrix,binaryRatingMatrix-method
Calculate the Prediction Error for a RecommendationcalcPredictionAccuracy calcPredictionAccuracy,realRatingMatrix,realRatingMatrix-method calcPredictionAccuracy,topNList,binaryRatingMatrix-method calcPredictionAccuracy,topNList,realRatingMatrix-method
Dissimilarity and Similarity Calculation Between Rating Datadissimilarity dissimilarity,binaryRatingMatrix-method dissimilarity,realRatingMatrix-method similarity similarity,ratingMatrix-method
Error CalculationError error frobenius MAE MSE RMSE
Evaluate a Recommender Modelsevaluate evaluate,evaluationScheme,character-method evaluate,evaluationScheme,list-method
Class "evaluationResultList": Results from Evaluating Multiple Recommender Methodsavg,evaluationResultList-method coerce,list,evaluationResultList-method evaluationResultList-class show,evaluationResultList-method [,evaluationResultList,ANY,missing,missing-method
Class "evaluationResults": Results of the Evaluation of a Single Recommender Methodavg avg,evaluationResults-method confusionMatrix-class evaluationResults-class getConfusionMatrix getConfusionMatrix,evaluationResults-method getModel getModel,evaluationResults-method getResults getResults,evaluationResults-method getRuns getRuns,evaluationResults-method show,evaluationResults-method
Creator Function for evaluationSchemeevaluationScheme evaluationScheme,ratingMatrix-method
Class "evaluationScheme": Evaluation SchemeevaluationScheme-class getData getData,evaluationScheme-method show,evaluationScheme-method
Funk SVD for Matrices with Missing DatafunkSVD predict.funkSVD
List and Data.frame Representation for Recommender Matrix ObjectsgetData.frame getData.frame,ratingMatrix-method getList getList,binaryRatingMatrix-method getList,realRatingMatrix-method getList,topNList-method
Create a Hybrid RecommenderHybridRecommender
Internal Utility FunctionsgetParameters internal internalFunctions returnRatings
Jester dataset (5k sample)Jester5k JesterJokes
MovieLense Dataset (100k)MovieLense MovieLenseMeta MovieLenseUser
Anonymous web data from www.microsoft.comMSWeb
Normalize the ratingsdenormalize denormalize,realRatingMatrix-method normalize normalize,realRatingMatrix-method
Plot Evaluation Resultsplot plot,evaluationResultList-method plot,evaluationResults-method
Predict Recommendationspredict predict,Recommender-method
Class "ratingMatrix": Virtual Class for Rating Datacoerce,ratingMatrix,data.frame-method coerce,ratingMatrix,list-method colCounts colCounts,ratingMatrix-method colMeans,ratingMatrix-method dim,ratingMatrix-method dimnames,ratingMatrix-method dimnames<-,ratingMatrix,list-method getNormalize getNormalize,ratingMatrix-method getRatingMatrix getRatingMatrix,ratingMatrix-method getRatings getRatings,ratingMatrix-method hasRating hasRating,ratingMatrix-method image,ratingMatrix-method nratings nratings,ratingMatrix-method ratingMatrix ratingMatrix-class rowCounts rowCounts,ratingMatrix-method rowMeans,ratingMatrix-method sample,ratingMatrix-method show,ratingMatrix-method [,ratingMatrix,ANY,ANY,ANY-method
Class "realRatingMatrix": Real-valued Rating Matrixbinarize binarize,realRatingMatrix-method coerce,data.frame,realRatingMatrix-method coerce,dgCMatrix,realRatingMatrix-method coerce,dgTMatrix,realRatingMatrix-method coerce,matrix,realRatingMatrix-method coerce,realRatingMatrix,data.frame-method coerce,realRatingMatrix,dgCMatrix-method coerce,realRatingMatrix,dgTMatrix-method coerce,realRatingMatrix,matrix-method coerce,realRatingMatrix,ngCMatrix-method colSds colSds,realRatingMatrix-method getTopNLists getTopNLists,realRatingMatrix-method realRatingMatrix realRatingMatrix-class removeKnownRatings removeKnownRatings,realRatingMatrix-method rowSds rowSds,realRatingMatrix-method [<-,realRatingMatrix,ANY,ANY,ANY-method
Create a Recommender ModelgetModel,Recommender-method Recommender Recommender,ratingMatrix-method recommenderRegistry
Class "Recommender": A Recommender ModelRecommender-class show,Recommender-method
Sparse Matrix Representation With NAs Not Explicitly StoreddropNA dropNA2matrix dropNAis.na sparseNAMatrix sparseNAMatrix-class
Class "topNList": Top-N ListbestN bestN,topNList-method c,topNList-method coerce,topNList,dgCMatrix-method coerce,topNList,dgTMatrix-method coerce,topNList,list-method coerce,topNList,matrix-method coerce,topNList,ngCMatrix-method coerce,topNList,realRatingMatrix-method colCounts,topNList-method length,topNList-method removeKnownItems removeKnownItems,topNList-method rowCounts,topNList-method show,topNList-method topNList topNList-class