Releases: EpistasisLab/tpot
Releases · EpistasisLab/tpot
v0.12.2
What's Changed
- estimator type by @perib in #1319
- Update requirements by @gatl in #1335
- Bump torch from 1.3.1 to 1.13.1 by @dependabot in #1336
- update sklearn version to 1.1.3 by @perib in #1337
- remove deprecated imp, fix docstring warning by @perib in #1331
- update compatibility with scikitlearn 1.4 by @perib in #1343
- Improve error message by @gatl in #1338
- Mate operator fix by @perib in #1268
New Contributors
- @gatl made their first contribution in #1335
- @dependabot made their first contribution in #1336
Full Changelog: v0.12.1...v0.12.2
Contributors
gatl, perib, and dependabot
Assets 2
v0.12.1
v0.12.0 release
- Fix numpy compatibility
- Dask optimizations
- Minor bug fixes
v0.11.7 minor release
- Fix compatibility issue with scikit-learn 0.24 and xgboost 1.3.0
- Fix a bug causing that TPOT does not work when classifying more than 50 classes
- Add initial support
Resamplerfromimblearn - Fix minor bugs
0.11.6.post3
- A patch to fix compatibility issues with the latest version of xgboost (v1.3.0)
v0.11.6.post2
- make XGBoost as a required dependency
v0.11.6.post1
- Refine the logic of checking the type of an operator.
Version 0.11.6
- Fix a bug causing point mutation function does not work properly with using
templateoption - Add a new built configuration called "TPOT cuML" which TPOT will search over a restricted configuration using the GPU-accelerated estimators in RAPIDS cuML and DMLC XGBoost. This configuration requires an NVIDIA Pascal architecture or better GPU with compute capability 6.0+, and that the library cuML is installed.
- Add string path support for log/log_file parameter
- Fix a bug in version 0.11.5 causing no update in stdout after each generation
- Fix minor bugs
Covariate adjustments branch
- Development branch based on TPOT 0.11.1 for adjusting covariate without data leakage.