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Changes in version 1.0.6
(09/19/2023)
- 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
(09/16/2023)
Bugfixes
- changed parameter name in interestMeasure().
- fixed issue with adding a single interest measure.
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 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
(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.
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)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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