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recommenderlab (version 0.1-9)
Lab for Developing and Testing Recommender Algorithms
Description
Provides a research infrastructure to test and develop recommender algorithms including UBCF, IBCF, FunkSVD and association rule-based algorithms.
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Install
install.packages('recommenderlab')
Monthly Downloads
2,656
Version
0.1-9
License
GPL-2
Maintainer
Michael Hahsler
Last Published
May 19th, 2016
Functions in recommenderlab (0.1-9)
Search functions
Error
Error Calculation
funkSVD
Funk SVD for Matrices with Missing Data
getList
List and Data.frame Representation for Recommender Matrix Objects
dissimilarity
Dissimilarity and Similarity Calculation Between Rating Data
ratingMatrix
Class "ratingMatrix": Virtual Class for Rating Data
MovieLense
MovieLense Dataset (100k)
Recommender
Create a Recommender Model
Jester5k
Jester dataset (5k sample)
plot
Plot Evaluation Results
MSWeb
Anonymous web data from www.microsoft.com
evaluationResults-class
Class "evaluationResults": Results of the Evaluation of a Single Recommender Method
predict
Predict Recommendations
normalize
Normalize the ratings
evaluationScheme
Creator Function for evaluationScheme
Recommender-class
Class "Recommender": A Recommender Model
binaryRatingMatrix
Class "binaryRatingMatrix": A Binary Rating Matrix
evaluationResultList-class
Class "evaluationResultList": Results of the Evaluation of a Multiple Recommender Methods
topNList
Class "topNList": Top-N List
sparseNAMatrix-class
Sparse Matrix Representation With NAs Not Explicitly Stored
calcPredictionAccuracy
Calculate the Prediction Error for a Recommendation
evaluationScheme-class
Class "evaluationScheme": Evaluation Scheme
realRatingMatrix
Class "realRatingMatrix": Real-valued Rating Matrix
evaluate
Evaluate a Recommender Models