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).

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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.

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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).

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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