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Releases: EpistasisLab/tpot

v0.12.2

23 Feb 19:05
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What's Changed

New Contributors

Full Changelog: v0.12.1...v0.12.2

v0.12.1

15 Aug 18:21
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Fixes issue with runs terminating too early

What's Changed

v0.12.0 release

25 May 22:44
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  • Fix numpy compatibility
  • Dask optimizations
  • Minor bug fixes

v0.11.7 minor release

06 Jan 15:19
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  • 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 Resampler from imblearn
  • Fix minor bugs

0.11.6.post3

14 Dec 15:07
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  • A patch to fix compatibility issues with the latest version of xgboost (v1.3.0)

v0.11.6.post2

30 Nov 16:31
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  • make XGBoost as a required dependency

v0.11.6.post1

05 Nov 15:52
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  • Refine the logic of checking the type of an operator.

Version 0.11.6

26 Oct 15:09
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  • Fix a bug causing point mutation function does not work properly with using template option
  • 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

02 Sep 20:35
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Pre-release
  • Development branch based on TPOT 0.11.1 for adjusting covariate without data leakage.

v0.11.5

01 Jun 22:10
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  • Make Pytorch as an optional dependency
  • Refine installation documentation