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Description du projet

MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms. It addresses the two most common scenarios in collaborative filtering: rating prediction (e.g. on a scale of 1 to 5 stars), and item prediction from implicit feedback (e.g. from clicks or purchase actions). It contains dozens of recommender engines, including state-of-the-art matrix factorization methods. It also supports real-time updates to the recommender engines, storing engines to disk and reloading them again, and several evaluation measures to compare the accuracy of different recommender system methods. Three command-line programs that offer most of the functionality contained in the library are included.

Système requise

System requirement is not defined
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2012-01-15 11:06 Retour à la liste release
2.03

Les calculs de similarité sont maintenant plus rapides et consomment moins de mémoire. Cette version ajoute le nouveau critère de prévision évaluation des cote CBD (plafonnée déviance binomiale), nouvelles décisionnaires (MultiCoreBPRMF et LogisticRegressionMatrixFactorization) et de corrections de bogues et d'autres améliorations pour les décisionnaires, BPRMF, MultiCoreMatrixFactorization, TimeAwareBaseline, UserItemBaseline et ItemKNNCosine.
Similarity computations are now faster and consume less memory. This release adds the new rating prediction evaluation criterion CBD (capped binomial deviance), new recommenders (MultiCoreBPRMF and LogisticRegressionMatrixFactorization), and bugfixes and other improvements for the recommenders BPRMF, MultiCoreMatrixFactorization, TimeAwareBaseline, UserItemBaseline, and ItemKNNCosine.

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