Changes in version 0.2-6 (06/16/2020)
New Features
- ratingMatrix gained method hasRatings.
- Recommender gained method “HYBRID” to create hybrid recommenders. Now hybrid recommenders can also be used in evaluate().
- similarity gained parameters min_matching and min_predictive.
Bugfixes
- predict for Recommender RANDOM now uses the correct user ids in the prediction (reported by aliko-str).
- fixed weight bug in Recommender UBCF (reported by aliko-str).
- Recommender UBCF now removes self-matches if item ids are specified in newdata. Specifying data in predict is no longer necessary. (reported by aliko-str).
- HybridRecommender now handles NAs in predictions correctly (was handled as 0).
Changes in version 0.2-5 (08/27/2019)
Changes
- predict with type “ratingMatrix” now returns predictions for the known ratings instead of replacing them with the known values.
- Recommender methods Popular, AR and RERECOMMENDER now also return ratings for binary data (and thus can be used for HybridRecommender).
- Added a LIBMF-based recommender.
Bugfixes
- evaluationScheme with negative numbers for given (all-but-x scheme) now works even if there are no given items left (reported by philippschmalen).
Changes in version 0.2-4 (03/23/2019)
Bugfixes
- Fixed bug in denormalization by column with z-score (reported by jackyrx).
- Fixed bug in predict with type “ratingMatrix” where known values were not denormalized (reported by MounirHader).
Changes in version 0.2-3 (06/19/2018)
Bugfixes
- Fixed bug in ALS_implicit (reported by equalise).
- getData for binaryRatingMatrix data with type “known” and “unknown” preserves now user ids/rownames (reported by Kasia Kulma).
- predict for HybridRecommender now retains user IDs (reported by homodigitus).
- Removed warning about using drop in subsetting ratingMatrices (reported by donnydongchen).
Changes in version 0.2-2 (04/05/2017)
Bugfixes
- predict for IBCF now returns top-N lists correctly.
- (cross) dissimilarity for binary data now returns the correct data type (reported by inkrement).
Changes in version 0.2-1 (09/15/2016)
New Features
- Added recommender method ALS and ALS_implicit based on latent factors and alternating least squares (contributed by Bregt Verreet).
- Changes in recommendation method AR: Default for maxlen is now 3 to find more specific rules. Parameters measure and decreasing for sorting the rule base are now called sort_measure and sort_decreasing. New parameter apriori_control can be used to pass a control list to apriori in arules.
- The registry now has a reference field.
Bugfixes
- Fixed bug in method IBCF with n being ignored in predict (reported by Giorgio Alfredo Spedicato).
Changes in version 0.2-0 (05/31/2016)
- Added recommender RERECOMMEND to recommend highly rated items again (e.g., movies to watch again).
- Added a hybrid recommender (HybridRecommender).
- realRatingMatrix supports now subset assignment with [.
- RECOM_POPULAR now shows the parameters in the registry.
- RECOM_RANDOM produced now random ratings from the estimated distribution of the available recommendations (from a normal distribution with the user’s means and standard deviation).
- predict now checks if newdata (number of items) is compatible with the model.
- getTopNLists and bestN gained a randomized argument to increase prediction diversity.
- Added getRatings method for topNList.
Changes in version 0.1-9 (05/18/2016)
- FIX: rownames of newdata are now preserved in prediction output.
- We use testthat now.
- Normalization now can be done on rows and columns at the same time.
- SVD with column-mean imputation now folds in new users.
- Added Funk SVD (funkSVD and recommender SVDF).
- Added function error measures: MAE, MSE, RMSE, frobenius (norm).
- Jester5k contains now the jokes.
- MovieLense contains now movie meta information.
- topNLists now also contains ratings.
- Removed obsolete PCA-based recommender.
Changes in version 0.1-8 (12/17/2015)
- Fixed several problems in the vignette.
- predict for realRatingMatrix accepts now type = “ratingMatrix” to returns a completed rating matrix.
- Negative values for given in evaluationScheme implement all-but-given evaluation.
- Method “SVD” used now EM-based approximation from package bcv.
Changes in version 0.1-7 (7/23/2015)
- NAMESPACE now imports non standard R packages.
Changes in version 0.1-5 (8/18/2014)
- Fixed NAMESPACE problems.
- Evaluation of ratings is now better integrated into evaluate.
- binarize keeps now dimnames.
Changes prior to 0.1-4 (1/11/2013)
Alpha version 0.1-0 (1/23/2010)