Releases: PreferredAI/cornac
Releases · PreferredAI/cornac
Cornac 1.6.1
New improvements
- Fix bug of Z dims in SoRec (#340)
- Add a reference to topic model in CTR (#341)
Cornac 1.6.0
New features
- Add Mean Average Precision (MAP) metric (#338)
Cornac 1.5.2
New improvements
- Fix bug in graph modality (#333)
- Update models to support clone function (#334)
- Add
lambda_reg
argument for NMF model (#335)
- Use
tqdm.auto
for multiple environment compatibility (#336)
Cornac 1.5.1
New improvements
- Improve the efficiency of KNN methods (#331)
- Use
tqdm.auto
for compatibility on Jupyter notebook env (#332)
Cornac 1.5.0
New models
- MTER model is faster with Cython (#320)
- Neighborhood-based methods (UserKNN and ItemKNN) (#329)
Cornac 1.4.1
New features and improvements
- Refactor code in examples (#317)
- CI tools support Python 3.7
- Update and test all tutorials and examples
Cornac 1.4.0
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)
Cornac 1.3.1
New features and improvements
- Add default attributes
total_users
and total_items
to Dataset
(#300)
Cornac 1.3.0
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)
Cornac 1.2.2
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)