NEWS
recommenderlab 1.0.6-1
- fixed crossref for package Matrix (reported by Mikael Jagan).
recommenderlab 1.0.6 (2023-09-20)
- fixed bug in row/colSums call for Matrix 1.6-2 (reported by Mikael Jagan).
- updated deprecated coercion for Matrix
recommenderlab 1.0.5 (2023-09-16)
Bugfixes
- changed parameter name in interestMeasure().
- fixed issue with adding a single interest measure.
recommenderlab 1.0.4 (2023-06-20)
Bugfixes
- added missing rmse function for funkSVD man page.
- test-recom.R: removed extra comma.
recommenderlab 1.0.3 (2023-01-21)
New Features
- evaluationScheme now drops users with too few ratings with a warning.
- evaluationScheme creation is now faster for realRatingMatrix.
Bugfixes
- Fixed issues with ratingMatrix with missing dimnames.
- UBCF does now also work for users with fewer than n nearest neighbors.
recommenderlab 1.0.2 (2022-08-17)
Internal Changes
- Preparations for changes in coercion for Matrix 1.4.2
recommenderlab 1.0.1 (2022-06-17)
Bugfixes
- Fixed similarity() and dissimilarity() after changes for Cosine in package proxy
(reported by Artur Gramacki).
- dropNA now always creates a dgCMatrix.
recommenderlab 1.0.0 (2022-05-27)
Bugfixes
- calcPredictionAccuracy now works with negative values for given (all-but-x). A negative value produces an error with instructions.
- We require now proxy version >= 0.4-26 which fixed a conversion bug for cosine similarity.
- RECOM_AR now respects already know items (code provided by gregreich).
- evaluate: keepModel = TRUE now works (bug reported by gregreich).
- Recom_SVD: fixed issue with missing values set to zero (bug reported by [email protected])
Changes
- Ratings of zero are now fully supported. We use .Machine$double.xmin to represent 0 in
sparse matices. zapsmall() can be used to change them back to 0.
- topNList has now a method c() to combine multiple lists.
- RECOM_AR: Ratings are now equal to quality measure used for ranking.
- HYBRIDRECOMMENDER: add "max" and "min" aggregation.
- removeKnownRatings is now sparse.
- RECOM_RANDOM now has parameter range to specify the rating range.
recommenderlab 0.2-7 (2021-02-26)
New Features
- The MovieLense data set includes now also user meta information.
Changes
- getConfusionMatrix() is deprecated. Use getResults() instead.
- added an example for how to evaluate hybrid recommenders.
- calcPredicition now also reports N.
- calcPredicition now stores the list length for multiple top-N lists as a column called n in the result (instead of using rownames).
Bugfixes
- UBCF for binary data: Fixed normalization for option weighted (reported by bhawwash).
- Fixed problems with less than k neighbors (reported by weiy6).
- Fixed incorrect description of comparisons in vignette.
recommenderlab 0.2-6 (2020-06-17)
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).
recommenderlab 0.2-5 (2019-08-27)
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).
recommenderlab 0.2-4 (2019-03-23)
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).
recommenderlab 0.2-3 (2018-06-19)
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).
recommenderlab 0.2-2 (2017-04-05)
Bugfixes
- predict for IBCF now returns top-N lists correctly.
- (cross) dissimilarity for binary data now returns the correct data
type (reported by inkrement).
recommenderlab 0.2-1 (2016-09-17)
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).
recommenderlab 0.2-0 (2016-06-01)
- 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.
recommenderlab 0.1-9 (2016-05-19)
- 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.
recommenderlab 0.1-8 (2015-12-18)
- 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.
recommenderlab 0.1-7 (2015-07-24)
- NAMESPACE now imports non standard R packages.
recommenderlab 0.1-5 (2014-08-18)
- Fixed NAMESPACE problems.
- Evaluation of ratings is now better integrated into evaluate.
- binarize keeps now dimnames.
recommenderlab 0.1-4 (2014-01-13)
recommenderlab 0.1-0 (2010-01-23)