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).

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.

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 [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 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.

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.

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

• 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).

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).

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).

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)

• 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.
• 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).