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README.md 2026-09-18 9.3 kB
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This release improves reproducibility and correctness across AutoML and tuning, including consistent random seed handling for SGD, logistic regression, random forest, and XGBoost, per-fold resampling for class imbalance, corrected quantized float sampling, per-metric trial averages, and preservation of zero-valued anonymous tuning metrics. It strengthens data preparation and evaluation with stable categorical encoding, aligned sample weights for non-shuffled and group splits, and free-memory propagation, while adding compatibility for recent scikit-learn and statsmodels changes. It corrects Statsmodels future forecast horizons and adds a Simplified Chinese README. It also adds Windows ARM64 CI, hardens GitHub Actions permissions and action pinning, and refreshes documentation and dependencies.

Thank you to all contributors for the PRs, issues, reviewing and testing.

Welcome @immu4989, @arpitjain099, @arushiiii18, @danfiedler-msft, @MeiSiristhebest, @AmirF194, @shoemoney, @VenishPaneliya, @nithin-aashik-mcw, @betacatsling, @wangyusheng1985, and @JasonYeYuhe to the community!

What's Changed

New Contributors

Full Changelog: https://github.com/microsoft/FLAML/compare/v2.6.0...v2.7.0

Source: README.md, updated 2026-09-18