v1.0.13

Highlights

• Logging the search_state.config directly to MLflow instead of key-dictionary pair
• Move searcher and scheduler into tune
• Move import location for Ray 2
• Fix NLP dimension mismatch bug

What's Changed

• Dockerfile building problem by @skzhang1 in #719
• Update Contribute.md by @vijaya-lakshmi-venkatraman in #716
• Move import location for Ray 2 by @sonichi in #721
• Fix issue 728 add hyperlink to GitHub location by @Libens-bufo in #731
• Update model.py by @vijaya-lakshmi-venkatraman in #739
• Issue724 by @liususan091219 in #745
• log search_state.config directly instead of under tag config by @prithvikannan in #747
• move searcher and scheduler into tune by @sonichi in #746
• updating the data collator for seq-regression to handle the dim mismatch problem by @liususan091219 in #751
• Update Contribute by @sonichi in #741
• Remove NLP classification head by @liususan091219 in #756

New Contributors

• @vijaya-lakshmi-venkatraman made their first contribution in #716
• @Libens-bufo made their first contribution in #731
• @prithvikannan made their first contribution in #747

Full Changelog: v1.0.12...v1.0.13

v1.0.12

Highlights

• Fix MLFlow bug to support the case where search.state.metric_for_logging is None
• Support customized cross-validation strategy
• Fix SARIMAX seasonal_order parameter name in the wrapper

Thanks to all the contributors for this release!

What's Changed

• chore: Auto update github actions with dependabot by @iemejia in #688
• talks and tutorials by @qingyun-wu in #694
• updating nlp notebook by @liususan091219 in #693
• "intermediate_results" TypeError: argument of type 'NoneType' is not iterable by @liususan091219 in #695
• Update Research.md by @sonichi in #701
• Bump actions/setup-node from 2 to 3 by @dependabot in #698
• Bump actions/cache from 1 to 3 by @dependabot in #696
• Support customized cross-validation strategy by @skzhang1 in #669
• Add $schema to cgmanifest.json by @JamieMagee in #708
• Fix SARIMAX seasonal_order parameter name in the wrapper by @EgorKraevTransferwise in #711

New Contributors

• @iemejia made their first contribution in #688
• @JamieMagee made their first contribution in #708
• @EgorKraevTransferwise made their first contribution in #711

Full Changelog: v1.0.11...v1.0.12

v1.0.11

Highlights

• Preserve the checkpoint when deleting AutoML objects.
• Create no eval set when setting use_best_model to False for catboost.

What's Changed

• add guideline collection by @qingyun-wu in #687
• LightGBM notebook update by @sonichi in #690
• Add preserve_checkpoint to preserve the checkpoint after del by @liususan091219 in #692
• use_best_model for catboost by @sonichi in #679

Full Changelog: v1.0.10...v1.0.11

v1.0.10

This release contains several new features to highlight:

• A major new feature is to support multiple time series in one dataset with a new task named "ts_forecast_panel" and a neural network estimator from pytorch-forecast.
• Allow disabling shuffle for custom splitter.
• Allow explicit specification of whether the choices of a hp have an inherent order.
• Allow skipping data transformation to avoid overhead.
• Support AzureML pipeline tuning.
• Allow log file name to be specified in tune.run and perform logging when ray is used.

There are other improvements for the transformer estimator and bug fixes for config constraints.

What's Changed

• Fixing the issue that FLAML trial number is significantly smaller than Transformers.hyperparameter_search by @liususan091219 in #657
• make test result more stable by @sonichi in #646
• Add pipeline tuner component and dependencies. by @ruizhuanguw in #671
• Skip transform by @jmrichardson in #665
• pull request template by @sonichi in #668
• Update Research.md by @liususan091219 in #672
• Documentation on search space and parallel/sequential tuning by @qingyun-wu in #675
• time series forecasting with panel datasets by @int-chaos in #541
• categorical choice can be ordered or unordered by @sonichi in #677
• Disable shuffle for custom CV by @jmrichardson in #659
• update time series forecast notebook by @int-chaos in #682
• check config constraints for the initial config by @sonichi in #685
• log_file_name in tune.run() by @sonichi in #681
• updating nlp notebook by @liususan091219 in #683
• VW version requirement and documentation on config_constraints vs metric_constraints by @qingyun-wu in #686

New Contributors

• @jmrichardson made their first contribution in #665

Full Changelog: v1.0.9...v1.0.10

v1.0.9

Highlight

• Add the feature names and importance in AutoML
• Update NLP search space and fix several bugs in NLP tasks
• Respect kwargs in AutoML.predict()

What's Changed

• Feature names and importances by @sonichi in #621
• fix NER roberta bug by @liususan091219 in #632
• updating search space by @liususan091219 in #633
• Bump terser from 5.10.0 to 5.14.2 in /website by @dependabot in #642
• This PR fixes the frequent NLP bugs in the other PRs by @liususan091219 in #647
• added "**kwargs" to "predict" by @zzheng93 in #641
• Fix alerts by @skzhang1 in #644
• Update .NET documentation by @luisquintanilla in #643
• Fix HPO evaluation bug by @liususan091219 in #645

New Contributors

• @dependabot made their first contribution in #642
• @zzheng93 made their first contribution in #641
• @luisquintanilla made their first contribution in #643

Full Changelog: v1.0.8...v1.0.9

v1.0.8

• Support latest xgboost version
• Reproducibility improvement for blendsearch
• Allow custom GroupKFold object as split_type
• Bug fix in token classification tasks such as NER
• Allow FLAML_sample_size in starting_points

What's Changed

• log msg about ensemble by @sonichi in #597
• support latest xgboost version by @sonichi in #599
• Fix automl settings in scikit-learn pipeline integration example by @ZviBaratz in #602
• update got version by @sonichi in #607
• min eci depends on cost_attr; cost_attr in ls by @sonichi in #612
• Replaced !pip calls with %pip magic command by @ZviBaratz in #604
• cath URLError by @sonichi in #613
• Updated pre-commit hooks by @ZviBaratz in #609
• Py36 by @sonichi in #614
• Allow custom GroupKFold object as split_type by @sonichi in #616
• Typo fix by @ZviBaratz in #618
• use relative url in doc by @sonichi in #620
• This PR will solve issue, code example format in the doc #622 by @31Sanskrati in #623
• fix ner bug; refactor post processing of TransformersEstimator prediction by @liususan091219 in #615
• isinstance(x, int) -> isinstance(x, (int, np.integer)) by @liususan091219 in #627
• Allow FLAML_sample_size in starting_points by @qingyun-wu in #619
• disable max_len for ner by @liususan091219 in #629
• fix #630 by @adi611 in #631

New Contributors

• @ZviBaratz made their first contribution in #602
• @31Sanskrati made their first contribution in #623
• @adi611 made their first contribution in #631

Full Changelog: v1.0.7...v1.0.8

v1.0.7

• Add support of Python 3.10.
• Enable ensemble when using ray.
• Enable nested tuning runs.
• Made BlendSearch reproducible when constructed outside tune.run().
• Fix resource limit issue in some macos version.
• Bug fix in nlp.
• Make set_search_properties() compatible with ray tune.

What's Changed

• enable ensemble when using ray by @sonichi in #583
• update time from start when using ray by @sonichi in #586
• Class variables, cost_attr, and reproducibility by @qingyun-wu in #587
• backup & recover global vars for nested tune.run by @sonichi in #584
• fixing a bug in nlp/utils.py by @liususan091219 in #590
• fix resource limit issue by @sonichi in #589
• Modified setup instructions by @daniel-555 in #593
• Add python 3.10 in the CI by @sonichi in #591
• trying to fix the indexerror for ner by @liususan091219 in #596
• Update documentation for NLP by @liususan091219 in #594
• set_search_properties by @sonichi in #595

New Contributors

• @daniel-555 made their first contribution in #593

Full Changelog: v1.0.6...v1.0.7

v1.0.6

What's Changed

• init value type match by @sonichi in #575

Full Changelog: v1.0.5...v1.0.6

v1.0.5

What's Changed

• fixing trainable and update function, completing NOTE by @liususan091219 in #566
• Update fit_kwargs_by_estimator example in Task-Oriented-AutoML.md by @liususan091219 in #561
• add zeroshot notebook by @sonichi in #569
• set holiday version <0.14 for prophet by @sonichi in #573
• Updated doc by @PrajwalBorkar in #572
• install openml for notebook example by @sonichi in #574

Full Changelog: v1.0.4...v1.0.5

v1.0.4

What's Changed

• Update documentation for FAQ about how to handle imbalanced data by @liususan091219 in #560
• update doc about scheduler exception by @sonichi in #564
• version update by @sonichi in #567

Full Changelog: v1.0.3...v1.0.4