add changelog entry for 1.2.4

CHANGELOG.md

@@ -1,6 +1,124 @@
 # Changelog
 
 The release log for Ax.
+## [1.2.4] -- Feb 24, 2026
+
+#### Bug Fixes
+* Fix incorrect feasibility computation when using `qLogProbabilityOfFeasibility` for MOO — objective weights were applied twice via both the posterior transform and the constraint matrix, leading to incorrect results when only objective thresholds (no outcome constraints) were present (#4935)
+* Add defensive `issubclass` guard for acquisition function dispatch to prevent silent fallthrough for future subclasses of `qLogProbabilityOfFeasibility` (#4938)
+
+#### Other changes
+* Remove unused `objective_thresholds` parameter from `Acquisition.get_botorch_objective_and_transform` — the parameter was silently discarded (#4939)
+* Add `Self` type annotations to clone methods for better type inference in subclasses (#4907)
+* Heterogeneous search space utilities for transfer learning benchmarks (#4767)
+* Migrate benchmarking state dict files for GPyTorch compatibility (#4916)
+
+## [1.2.3] -- Feb 19, 2026
+
+#### Breaking Changes
+
+**Requirements**
+* Python 3.11+ required (#4810)
+* Pandas 3.0 upgrade (#4838)
+* BoTorch 0.17.0 (#4911)
+
+**API Removals**
+* `transition_to` now required on `TransitionCriterion` (#4848) — Users must explicitly specify transition targets
+* Removed callable serialization (#4806) — Encoding callables now raises an exception
+* Removed legacy classes: `TData` (#4771), `MinimumTrialsInStatus` (#4786), completion criteria (#4850), `arms_per_node` override (#4822)
+
+#### New Features
+* **Experiment Lifecycle Tracking**: New `ExperimentStatus` enum (`DRAFT`, `INITIALIZATION`, `OPTIMIZATION`, `COMPLETED`) with automatic status updates from the Scheduler based on generation strategy phase (#4737, #4738, #4891)
+* **BOPE (Preference Learning)**: Utility-based traces via PairwiseGP preference models (#4792); `UtilityProgressionAnalysis` support with "User Preference Score" UI (#4793)
+* **BONSAI (Pruning)**: New `pruning_target_parameterization` API parameter (#4775); tutorial and documentation added (#4865, #4871)
+* `add_tracking_metrics()` method (#4858)
+* `TorchAdapter.botorch_model` convenience property (#4827)
+* `DerivedParameter` now supports `bool` and `str` types (#4847)
+* LLM integration: `LLMProvider`/`LLMMessage` abstractions and `llm_messages` on Experiment (#4826, #4904)
+* Improved slice/contour plots: uses status_quo, best trial, center hierarchy (#4841)
+* Sensitivity analysis excludes 'step' by default (#4777)
+* `ScalarizedOutcomeConstraint` support in feasibility analysis (#4856)
+
+#### Performance
+* `DataRow`-backed `Data` class with itertuples — 3.6x faster tensor creation (#4773, #4774, #4798)
+* Generation strategy caching: significant speedup in high trial count regimes (#4830)
+* Optimization complete logic: O(nodes x TC) to O(TC on current node) (#4828)
+
+#### Bug Fixes
+* Fix `GeneratorRun.clone()` not copying metadata (mutations affected original) (#4892)
+* Fix OneHot transform not updating hierarchical parameter dependents (#4825)
+* Fix Float parameters loaded as ints from SQA (#4853)
+* Fix scikit-learn 1.8.0 compatibility with XGBoost (#4816)
+* Trials now marked ABANDONED (not FAILED) on metric fetch failure (#4779)
+* Baseline improvement healthcheck now shows WARNING instead of FAIL (#4883)
+
+#### Other changes
+* Codebase updated to Python 3.11+ idioms: `typing.Self` (#4867), `StrEnum` (#4868), `ExceptionGroup` (PEP 654) (#4877), `asyncio.TaskGroup` (#4878), PEP 604 type annotations (#4912)
+* For the complete list of 90+ PRs, see the [GitHub releases page](https://github.com/facebook/Ax/releases)
+
+## [1.2.2] -- Jan 2026
+
+NOTE: This will be the last Ax release before SQLAlchemy becomes a required dependency.
+
+#### Deprecations
+* Add deprecation warning to AxClient (#4749)
+* Add deprecation warning to 'optimize' loop API (#4697)
+* Deprecate Trial.runner (#4460)
+* Deprecate TensorboardMetric's `percentile` in favor of `quantile` (#4676)
+* Deprecate default_data_type argument to Experiment (#4698)
+
+#### New Features
+* Efficient leave-one-out cross-validation for Gaussian processes (#4631)
+* Add patience parameter to PercentileEarlyStoppingStrategy (#4595)
+* Log-scale support for ChoiceParameter (#4591)
+* Support ChoiceParameter in Log transform (#4592)
+* Add robust trial status polling to Orchestrator (#4756)
+* Expose validation for TL experiments and fetching of candidate TL sources through AxService (#4615)
+* Add PreferenceOptimizationConfig with storage layer support (#4638)
+* Add PLBO transform and metric ordering validation (#4633)
+* Add expect_relativized_outcomes flag to PreferenceOptimizationConfig (#4632)
+* Add kendall tau rank correlation diagnostic (#4617)
+* Vectorize SearchSpace membership check for performance (#4762)
+
+#### Analyses
+* New UtilityProgression Analysis for tracking optimization progress over time (#4535)
+* New Best Trials Analysis for identifying top-performing trials (#4545)
+* New Early Stopping Healthcheck analysis (#4569)
+* New Predictable Metrics Healthcheck analysis (#4598)
+* New Baseline Improvement Healthcheck analysis (#4673)
+* New Complexity Rating Healthcheck for assessing optimization difficulty (#4556)
+* Analysis to visualize experiment generation strategy (#4759)
+* Add Pareto frontier display on MOO objective scatter plots (#4708)
+* Add Progression Plots for MapMetric experiments to ResultsAnalysis (#4705)
+* Add SEM display option to ContourPlot (#4690)
+* Add markers to ProgressionPlot line charts (#4693)
+* GraphvizAnalysisCard and HierarchicalSearchSpaceGraph visualization (#4616)
+* IndividualConstraintsFeasibilityAnalysis replaces ConstraintsFeasibilityAnalysis (#4527)
+
+#### Bug Fixes
+* Fix tied trial bug in PercentileESS: use rank() for n_best_trial protection (#4587)
+* Fix StandardizeY not updating weights in ScalarizedObjective (#4619)
+* Fix StratifiedStandardizeY behavior with ScalarizedObjective & ScalarizedOutcomeConstraint (#4621)
+* Fix floating point precision issue in step_size validation (#4604)
+* Fix progression normalization logic in early-stopping strategies (#4525)
+* Fix dependent parameter handling in Log transform (#4679)
+* Drop NaN values in MAP_KEY column before align_partial_results (#4634)
+* Filter failed trials from plots (#4725)
+* Allow single progression early stopping checks when patience > 0 (#4635)
+* Update SOBOL transition criterion to exclude ABANDONED and FAILED trials (#4776)
+
+#### Other changes
+* Speed up MapDataReplayMetric (#4654)
+* Fast MapData.df implementation (#4487)
+* Validate patience <= min_progression in PercentileEarlyStoppingStrategy (#4639)
+* Enforce `smoothing` in `[0, 1)` for TensorBoardMetric (#4661)
+* Enforce sort_values=True for numeric ordered ChoiceParameter (#4597)
+* Add error if PowerTransformY is used with ScalarizedObjective (#4622)
+* Support ScalarizedObjective in get_best_parameters with model predictions (#4594)
+* Rename model_kwargs -> generator_kwargs (#4668)
+* Rename model_gen_kwargs -> generator_gen_kwargs (#4667)
+* Rename model_cv_kwargs -> cv_kwargs (#4669)
+
 ## [1.2.1] -- Nov 21, 2025
 #### Bug fixes
 * Improved error messaging for `client.compute_analyses` when certain analyses are