v0.6.0

[sonichi]

In this release, we added support for time series forecasting task and NLP model fine tuning. Also, we have made a large number of feature & performance improvements.

• data split by 'time' for time-ordered data, and by 'group' for grouped data.
• support parallel trials and random search in AutoML.fit() API.
• support warm-start in AutoML.fit() by using previously found start points.
• support constraints on training/prediction time per model.
• new optimization metric: ROC_AUC for multi-class classification, MAPE for time series forecasting.
• utility functions for getting normalized confusion matrices and multi-class ROC or precision-recall curves.
• automatically retrain models after search by default; options to disable retraining or enforce time limit.
• CFO supports hierarchical search space and uses points_to_evaluate more effectively.
• variation of CFO optimized for unordered categorical hps.
• BlendSearch improved for better performance in parallel setting.
• memory overhead optimization.
• search space improvements for random forest and lightgbm.
• make stacking ensemble work for categorical features.
• python 3.9 support.
• experimental support for automated fine-tuning of transformer models from huggingface.
• experimental support for time series forecasting.
• warnings to suggest increasing time budget, and warning to inform users there is no performance improvement for a long time.

Minor updates

• make log file name optional.
• notebook for time series forecasting.
• notebook for using AutoML in sklearn pipeline.
• bug fix when training_function returns a value.
• support fixed random seeds to improve reproducibility.
• code coverage improvement.
• exclusive upper bounds for hyperparameter type randint and lograndint.
• experimental features in BlendSearch.
• documentation improvement.
• bug fixes for multiple logged metrics in cv.
• adjust epsilon when time per trial is very fast.

Contributors

• @sonichi
• @qingyun-wu
• @int-chaos
• @liususan091219
• @Yard1
• @bnriiitb
• @su2umaru
• @eduardobull
• @sek788432
• @ekzhu
• @anshumandutt
• @yue-msr
• @sadtaf
• @fzanartu
• @dsbyprateekg
• @hanhanwu
• @PardeepRassani
• @gianpdomiziani
• @stepthom
• @anhnht3
• @zzheng93
• @flippercy
• @luizhemelo
• @nabalamu
• @lostmygithubaccount
• @suryajayaraman

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This discussion was created from the release v0.6.0.