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Releases: Adversarian/RACER

v1.2.1

12 Sep 20:15
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v1.2.0

04 Aug 11:32
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  • RACERPreprocessor now uses Scikit-learn's OneHotEncoder and LabelBinarizer by default. You may use fit_transform_pandas to use the pandas version of the encoding. However, be advised that the newly added fit and transform methods still use OneHotEncoder (for features) and LabelBinarizer (for targets).
  • Fixed several issues with the automatic classification task inference.
  • Marginally improved overall performance courtesy of Scikit-learn's optimized categorical encoders.

Full Changelog: v1.1.3...v1.2.0

v1.1.3

22 Jul 11:03
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v1.1.2

22 Jul 08:57
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v1.1.1

21 Jul 07:59
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v1.1.0

20 Jul 19:23
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Full Changelog: v1.0.3...v1.1.0

v1.0.3

20 Jul 01:48
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Full Changelog: v1.0.2...v1.0.3

Zenodo dummy release

17 Jul 15:09
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Zenodo dummy release Pre-release
Pre-release

This is a dummy release for Zenodo DOI generation.

v1.0.2

16 Jul 21:09
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v1.0.1

16 Jul 15:51
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Full Changelog: v1.0.0...v1.0.1