v0.13.0

Summary

This release introduces a new method implementation, PrototypeRepresentationLearner,
which is based on the work of Zemel et al. (2013) [paper link].
You can learn more about it in the documentation.

Additionally, this release includes several improvements to existing functionality:
enhanced support for relaxed constraints and multi-dimensional input data in optimization methods,
performance improvements through vectorization, updated supported Python versions
(removed 3.8, added 3.12), first steps toward Narwhals integration,
removal of unused functionality, and cleanup of local logging initialization.

🧠 New methods

• Implemented PrototypeRepresentationLearner, introduced in Zemel et al. (2013)
  (PR [#1478]) by @taharallouche

✨ New features

• Allowed relaxed constraints (except equalized_odds) in ThresholdOptimizer
  (PR [#1453]) by @taharallouche
• Allowed multi-dimensional input data X (ndims > 2) in ThresholdOptimizer and ExponentiatedGradient
  (PR [#1470]) by @taharallouche

⚡ Performance improvements

• Vectorized the curve interpolation step in ThresholdOptimizer to improve performance and readability
  (PR [#1448]) by @taharallouche

🐋 Narwhals integration

• Made the preprocessing module dataframe-agnostic through Narwhals
  (PR [#1525]) by @FBruzzesi
• Made the AnnotatedMetricFunction class dataframe-agnostic through Narwhals
  (PR [#1545]) by @FBruzzesi

🧹 Other improvements

• Removed support for Python 3.8 and added support for Python 3.12
  (PR [#1488]) by @tamaraatanasoska
• Removed the keyword argument control_features from ErrorRate.load_data,
  since it was non-functional for the method
  (PR [#1531]) by @StefanieSenger
• Removed local logging using environment variable FAIRLEARN_LOGS at initialization
  (PR [#1561]) by @parulgupta1004

New Contributors

• @anhpnv made their first contribution in https://github.com/fairlearn/fairlearn/pull/1460
• @nnpereira made their first contribution in https://github.com/fairlearn/fairlearn/pull/1466
• @emma-carballal made their first contribution in https://github.com/fairlearn/fairlearn/pull/1501
• @mosalah16 made their first contribution in https://github.com/fairlearn/fairlearn/pull/1507
• @dx9240 made their first contribution in https://github.com/fairlearn/fairlearn/pull/1509
• @camilasan made their first contribution in https://github.com/fairlearn/fairlearn/pull/1508
• @HDMax93 made their first contribution in https://github.com/fairlearn/fairlearn/pull/1513
• @Dimi-G made their first contribution in https://github.com/fairlearn/fairlearn/pull/1511
• @melekergin made their first contribution in https://github.com/fairlearn/fairlearn/pull/1514
• @milenaarneschedle made their first contribution in https://github.com/fairlearn/fairlearn/pull/1515
• @keshav-42 made their first contribution in https://github.com/fairlearn/fairlearn/pull/1524
• @StefanieSenger made their first contribution in https://github.com/fairlearn/fairlearn/pull/1527
• @Mariam-ke made their first contribution in https://github.com/fairlearn/fairlearn/pull/1536
• @FBruzzesi made their first contribution in https://github.com/fairlearn/fairlearn/pull/1525
• @KandiSanjana made their first contribution in https://github.com/fairlearn/fairlearn/pull/1549

Returning Contributors

• @alliesaizan
• @EdAbati
• @parulgupta1004
• @taharallouche
• @TamaraAtanasoska

Full Changelog: https://github.com/fairlearn/fairlearn/compare/v0.12.0...v0.13.0