v0.5.2

What's Changed

• Add HalvingModelSearchCV by @joaopfonseca in #68
• Add Gallery to documentation by @joaopfonseca in #69
• Add python 3.13 support by @joaopfonseca in #74

Full Changelog: v0.5.1...v0.5.2

v0.5.1

Full Changelog: v0.5.0...v0.5.1

v0.5.0

What's Changed

• [MRG] Add changelog generator by @joaopfonseca in #46
• Add CONTRIBUTING.md file by @joaopfonseca in #48
• Make rich an optional dependency by @joaopfonseca in #50
• Set utils.parallel_loop to track job completions and replace dependency rich with tqdm by @joaopfonseca in #52
• Refactor code to fix make code-analysis warnings by @joaopfonseca in #58
• Add mlresearch.show_versions() function by @joaopfonseca in #59
• Update pandas minimum dependencies (fixed error on make_mean_sem_table) by @joaopfonseca in #62
• Synthetic data quality metrics by @joaopfonseca in #64

Full Changelog: v0.4.2...v0.5.0

v0.4.2

Bug fixes.

Full Changelog: v0.4.1...v0.4.2

v0.4.1

What's Changed

• Several improvements to the datasets submodule
• [MRG] Add Python 3.11 support by @joaopfonseca in #24
• add check_random_state to init.py in utils and update docs by @ArcturusMotors in #38

New Contributors

• @ArcturusMotors made their first contribution in #38

Full Changelog: v0.4.0...v0.4.1

v0.4.0

What's Changed

• Move all CI/CD to GitHub Actions by @joaopfonseca in #13
• [MRG] Add more utilities to dataset functions by @joaopfonseca in #14
• [MRG] Improvements to datasets submodule by @joaopfonseca in #26
• [MRG] Add wrapper to encode categorical features in a pipeline by @joaopfonseca in #27
• [MRG] Move latex functions to its own module by @joaopfonseca in #30

Full Changelog: v0.3.4...v0.4.0

v0.4a2

NOTE: This pre-release contains implementations of algorithms for Self-supervised learning (BYOL and SimSiam). This release also contains objects to download image data from Pytorch and general definitions for image augmentations. They will be removed in the next release since:

1. I'm not going to used these methods anytime soon and I don't have the time to test them properly
2. They are out of scope of the library. It is meant to be used for machine learning techniques, focused on tabular data. In the future it may be worth considering the development of another library for computer vision, for example.
3. Setting Pytorch as a dependency for a reduced part of the library isn't particularly efficient.

Full Changelog: v0.4a1...v0.4a2

v0.4a1

Full Changelog: 0.1.0...v0.4a1

v0.3.4

Full Changelog: v0.3.3...v0.3.4

v0.3.3

Full Changelog: v0.3.2...v0.3.3