Man pages for mhahsler/recommenderlab
Lab for Developing and Testing Recommender Algorithms

binaryRatingMatrix-classClass "binaryRatingMatrix": A Binary Rating Matrix
calcPredictionAccuracyCalculate the Prediction Error for a Recommendation
dissimilarityDissimilarity and Similarity Calculation Between Rating Data
errorError Calculation
evaluateEvaluate a Recommender Models
evaluationResultList-classClass "evaluationResultList": Results of the Evaluation of a...
evaluationResults-classClass "evaluationResults": Results of the Evaluation of a...
evaluationSchemeCreator Function for evaluationScheme
evaluationScheme-classClass "evaluationScheme": Evaluation Scheme
funkSVDFunk SVD for Matrices with Missing Data
getListList and Data.frame Representation for Recommender Matrix...
HybridRecommenderCreate a Hybrid Recommender
internalInternal Utility Functions
Jester5kJester dataset (5k sample)
MovieLenseMovieLense Dataset (100k)
MSWebAnonymous web data from
normalizeNormalize the ratings
plotPlot Evaluation Results
predictPredict Recommendations
ratingMatrix-classClass "ratingMatrix": Virtual Class for Rating Data
realRatingMatrix-classClass "realRatingMatrix": Real-valued Rating Matrix
RecommenderCreate a Recommender Model
Recommender-classClass "Recommender": A Recommender Model
sparseNAMatrixSparse Matrix Representation With NAs Not Explicitly Stored
topNList-classClass "topNList": Top-N List
mhahsler/recommenderlab documentation built on Nov. 9, 2017, 4:20 p.m.