0.6.16

Changed the version of black in setup.py compared to 0.6.15.

0.6.15

• Add support for scikit-learn 1.1
• Add lower and upper bound constraints for scikit-learn to help suggest recommended versions
• Add support for newer versions of XGBoost

0.6.14

Updated metrics to handle y as DataFrame.

0.6.13

Release for the KDD'22 tutorial

0.6.12

Hands-on tutorials for KDD'22: https://github.com/IBM/lale/tree/master/examples/kdd22

0.6.11

1. RASL: balanced accuracy, balanced_accuracy_and_di
2. Documentation improvements
3. lale.lib.autoai_libs.DateTransformer

0.6.10

Fixes and changes to RASL, lale.lib.aif360 and import and export from sklearn.

0.6.9

1. rasl fixes
2. a fix for autoai_ts_libs
3. a change to Hyperopt's fit to accept a validation dataset.

0.6.8

1. Batching can handle an iterable or data loader without knowing n_batches.
2. XGBoost 1.6
3. pretty_print lists a list of external modules in wrap_imported_operators.

0.6.7

1. Batching changes to use task graphs
2. Removed autoai_ts_libs operators
3. BatchedTreeEnsemble estimators from SnapML
4. New rasl operators such as BatchedBaggingClassifier and HashingEncoder
5. Spilling in task graphs