Cornac

New models and datasets

- Weighted Bayesian Personalized Ranking (WBPR) model (309)
- Maximum Margin Matrix Factorization (MMMF) model (310)

New features and improvements

- Reset random number generator for reproducibility (301)
- Fix issue in NCRR metric (313)
- Use C++ Boost Random library for reproducibility across platforms (315)
- Support model saving and loading (316)

New features and improvements

- Add default attributes `total_users` and `total_items` to `Dataset` (300)

New models and datasets

- MovieLens 10M and 20M datasets (291)

New features and improvements

- Standardize datasets `load_feedback()` API (278)
- Add hyperopt for hyper-parameter tuning (286)
- Show validation results (optional) if exists (289)
- Update `Recommender.rank()` to support unknown item scores (283)
- Support multiple values of K for ranking metrics (297)
- Tutorial on how to work with auxiliary data (264)
- Tutorial on hyperparameter search for VAECF (290)
- Examples for VAECF, VMF, and SoRec (272, 276, 287)

New features and improvements

- Add `FilmTrust` dataset (266)
- Update `MCF`, `C2PF`, and `SoRec` models for the compatibility (261, 262)
- Support retrieving node degree in `GraphModality` (267)

New features and improvements

- Support `UIRT` data format (252)
- Fix bug in AUC metric (256)
- Tutorial on contributing an evaluation metric (258)

New models

- Multi-Task Explainable Recommendation (MTER) (238)
- Most Popular (MostPop) ranking baseline (244)
- Global Average (GlobalAvg) rating baseline (245)

New features and improvements

- Update VAECF model (237)
- `normalize()` function in utils (248)
- `TfidfVectorizer` in `TextModality` (249)