Changes in version 1.0.7 (2025-05-31) - slightly better handling of 0 vs. NA in sparse matrices. - coercion data.frame -> realRatingMatrix: added drop = TRUE so it works with tidyverse tibbles (reported by youngroklee-ml) Bugfixes - fixed crossref for package Matrix (reported by Mikael Jagan). - Fix for dissimilarity (which -> items) change in package arules. Changes in version 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 Changes in version 1.0.5 (2023-09-16) Bugfixes - changed parameter name in interestMeasure(). - fixed issue with adding a single interest measure. Changes in version 1.0.4 (2023-06-20) Bugfixes - added missing rmse function for funkSVD man page. - test-recom.R: removed extra comma. Changes in version 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. Changes in version 1.0.2 (2022-08-17) Internal Changes - Preparations for changes in coercion for Matrix 1.4.2 Changes in version 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. Changes in version 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 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 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. Changes in version 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. Changes in version 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). Changes in version 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). Changes in version 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). Changes in version 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). Changes in version 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). Changes in version 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). Changes in version 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. Changes in version 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. Changes in version 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. Changes in version 0.1-7 (2015-07-24) - NAMESPACE now imports non standard R packages. Changes in version 0.1-5 (2014-08-18) - Fixed NAMESPACE problems. - Evaluation of ratings is now better integrated into evaluate. - binarize keeps now dimnames. Changes in version 0.1-4 (2014-01-13) - Many. Changes in version 0.1-0 (2010-01-23)