Package: recommenderlab 1.0.6
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:
recommenderlab_1.0.6.tar.gz
recommenderlab_1.0.6.zip(r-4.5)recommenderlab_1.0.6.zip(r-4.4)recommenderlab_1.0.6.zip(r-4.3)
recommenderlab_1.0.6.tgz(r-4.4-any)recommenderlab_1.0.6.tgz(r-4.3-any)
recommenderlab_1.0.6.tar.gz(r-4.5-noble)recommenderlab_1.0.6.tar.gz(r-4.4-noble)
recommenderlab_1.0.6.tgz(r-4.4-emscripten)recommenderlab_1.0.6.tgz(r-4.3-emscripten)
recommenderlab.pdf |recommenderlab.html✨
recommenderlab/json (API)
NEWS
| # 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
- Jester5k - Jester dataset
- JesterJokes - Jester dataset
- MSWeb - Anonymous web data from www.microsoft.com
- MovieLense - MovieLense Dataset
- MovieLenseMeta - MovieLense Dataset
- MovieLenseUser - MovieLense Dataset
collaborative-filteringrecommender-system
Last updated 4 months agofrom:7f2fc10fff. Checks:OK: 5 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 25 2024 |
| R-4.5-win | NOTE | Nov 25 2024 |
| R-4.5-linux | NOTE | Nov 25 2024 |
| R-4.4-win | OK | Nov 25 2024 |
| R-4.4-mac | OK | Nov 25 2024 |
| R-4.3-win | OK | Nov 25 2024 |
| R-4.3-mac | OK | Nov 25 2024 |
Exports:avgbestNbinarizecalcPredictionAccuracycoercecolCountscolSdsdenormalizedissimilaritydropNAdropNA2matrixdropNAis.naevaluateevaluationSchemefrobeniusfunkSVDgetConfusionMatrixgetDatagetData.framegetListgetModelgetNormalizegetParametersgetRatingMatrixgetRatingsgetResultsgetRunsgetTopNListshasRatingHybridRecommenderimageMAEMSEnormalizenratingsplotpredictRecommenderrecommenderRegistryremoveKnownItemsremoveKnownRatingsreturnRatingsRMSErowCountsrowSdssampleshowsimilaritysummary
Dependencies:arulesfloatgenericsirlbalatticeMatrixmatrixStatsproxyRcppRcppProgressrecosystemregistry
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Class "binaryRatingMatrix": A Binary Rating Matrix | binaryRatingMatrix 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 Recommendation | calcPredictionAccuracy calcPredictionAccuracy,realRatingMatrix,realRatingMatrix-method calcPredictionAccuracy,topNList,binaryRatingMatrix-method calcPredictionAccuracy,topNList,realRatingMatrix-method |
| Dissimilarity and Similarity Calculation Between Rating Data | dissimilarity dissimilarity,binaryRatingMatrix-method dissimilarity,realRatingMatrix-method similarity similarity,ratingMatrix-method |
| Error Calculation | frobenius MAE MSE RMSE |
| Evaluate a Recommender Models | evaluate evaluate,evaluationScheme,character-method evaluate,evaluationScheme,list-method |
| Class "evaluationResultList": Results of the Evaluation of a Multiple Recommender Methods | avg,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 Method | avg 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 evaluationScheme | evaluationScheme evaluationScheme,ratingMatrix-method |
| Class "evaluationScheme": Evaluation Scheme | evaluationScheme-class getData getData,evaluationScheme-method show,evaluationScheme-method |
| Funk SVD for Matrices with Missing Data | funkSVD predict.funkSVD |
| List and Data.frame Representation for Recommender Matrix Objects | getData.frame getData.frame,ratingMatrix-method getList getList,binaryRatingMatrix-method getList,realRatingMatrix-method getList,topNList-method |
| Create a Hybrid Recommender | HybridRecommender |
| Internal Utility Functions | getParameters returnRatings |
| Jester dataset (5k sample) | Jester5k JesterJokes |
| MovieLense Dataset (100k) | MovieLense MovieLenseMeta MovieLenseUser |
| Anonymous web data from www.microsoft.com | MSWeb |
| Normalize the ratings | denormalize denormalize,realRatingMatrix-method normalize normalize,realRatingMatrix-method |
| Plot Evaluation Results | plot plot,evaluationResultList-method plot,evaluationResults-method |
| Predict Recommendations | predict predict,Recommender-method |
| Class "ratingMatrix": Virtual Class for Rating Data | coerce,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 Matrix | binarize 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 Model | getModel,Recommender-method Recommender Recommender,ratingMatrix-method recommenderRegistry |
| Class "Recommender": A Recommender Model | Recommender-class show,Recommender-method |
| Sparse Matrix Representation With NAs Not Explicitly Stored | dropNA dropNA2matrix dropNAis.na |
| Class "topNList": Top-N List | bestN 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 |
