Recent Releases of recommenderlab
recommenderlab -
Bugfixes
- changed parameter name in interestMeasure().
- fixed issue with adding a single interest measure.
- fixed bug in row/colSums call for Matrix (reported by Mikael Jagan).
- R
Published by mhahsler over 2 years ago
recommenderlab -
Changes in version 1.0.4 (06/20/2023)
Bugfixes
- added missing rmse function for funkSVD man page.
- test-recom.R: removed extra comma.
Changes in version 1.0.3 (01/20/2023)
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.
- R
Published by mhahsler over 2 years ago
recommenderlab -
Changes in version 1.0.2 (08/17/2022)
Internal Changes
- Preparations for changes in coercion for Matrix 1.4.2
Changes in version 1.0.1 (06/17/2022)
Bugfixes
- Fixed similarity() and dissimilarity() after changes for Cosine in package proxy (reported by Artur Gramacki).
- dropNA now always creates a dgCMatrix.
Changes in version 1.0.0 (05/27/2022)
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 jpbrooks@vcu.edu)
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 measures used for ranking.
- HYBRIDRECOMMENDER: add "max" and "min" aggregation.
- removeKnownRatings is now sparse.
- RECOM_RANDOM now has a parameter range to specify the rating range.
- R
Published by mhahsler over 3 years ago
recommenderlab -
Changes in version 0.2-7 (04/26/2021)
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.
- R
Published by mhahsler almost 5 years ago
recommenderlab -
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 minmatching and minpredictive.
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).
- R
Published by mhahsler over 5 years ago
recommenderlab -
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 not given items left (reported by philippschmalen).
- R
Published by mhahsler over 6 years ago
recommenderlab -
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).
- R
Published by mhahsler almost 7 years ago
recommenderlab -
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).
- R
Published by mhahsler over 7 years ago
recommenderlab -
Bugfixes
- predict for IBCF now returns top-N lists correctly.
- (cross) dissimilarity for binary data now returns the correct data type (reported by inkrement).
- R
Published by mhahsler almost 9 years ago
recommenderlab -
Changes in version 0.2-1 (09/15/2016)
- 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 sortmeasure and sortdecreasing. New parameter apriori_control can be used to pass a control list to apriori in arules.
- The registry now has a reference field.
- Added recommender method ALS and ALS_implicit based on latent factors and alternating least squares (contributed by Bregt Verreet).
- Fixed bug in method IBCF with n being ignored in predict (reported by Giorgio Alfredo Spedicato).
- R
Published by mhahsler over 9 years ago
recommenderlab -
- 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.
- R
Published by mhahsler over 9 years ago