Releases: kakao/buffalo
Releases · kakao/buffalo
Release 1.1.1
WARNING: THIS IS BROKEN VERSION
Bug Fixes
- Fix failure with creating a large database
- Fix bug that get_most_similar_item returns Nan values.
Misc
- Clean Code(Linting, Refactoring)
- Add new Jupiter example explaining large scale recommendation with Buffalo
Release 1.1.0
Update
-
Add CUDA accelerated BPR-MF
sample usage- When tested against ml-20m and Kakao Brunch Dataset, CUDA version of BPR-MF was about 5x times faster than CPU implementation of BPR-MF in training time.
-
Add metric truncated AUC
-
Update documents
Bug fixes
- Fix SGD update of BPR
- Fix to use bias when calculating top-k recommendation in BPR-MF
Misc
- Clean code(linting, refactoring)
- Add internal data type check and state check
- Change validation format to be CSR matrix
- Validation took about 40% faster than the previous version.
- but this might be harmful because it requires larger memory during validation.
Release 1.0.10
Bug Fixes
- hotfix, backward compatibility for pbar, iter_pbar
Release 1.0.9
Bug Fixes
- Fix numerical error when calculating training loss in conjugate gradient method(CPU implementation only)
- Fix broken print out for progress bar.
Release 1.0.8
Misc
- No longer need root permission for installation.
Release 1.0.7
Bug Fixes
- Correct illegal Python Index Package(PIP). (Added missing files to MANIFEST)
Misc
- Apply #10
- Update unittest for travis-ci environments.
Release 1.0.6
Misc
- Added travis-ci (WIP)
- Added examples/Dockerfile #7
- Correct stream default option(disable sppmi)
Release v1.0.5
Misc
- Fix memory corruption error when using optimize feature of ALS
- Correct typos
Release 1.0.4
Misc
- Now buffalo can be installed with Python Package Index.
pip install buffalo
- Added ld.conf.d/buffalo.pc.