0.7.6

• suppress warnings from AIF360 when tempeh or fairlearn are not installed
• support np.bool_ in JSON schema validation and lale.lib.aif360
• eliminate duplicates in lale.lib.autogen to make it easier to maintain

0.7.5

• Rewrite import_from_sklearn_pipeline, reducing copying and calls to set_params
• update black version used for formatting code to 2023 standard
• Improvements to monoidal TargetEnoder implementation
• minor improvement to task graph code

0.7.4

• Add support for scikit-learn 1.2.0
• Add a monoidal version of TargetEncoder
• Simplify import_from_sklearn_pipeline and improve how it works with higher order operators
• Fix spark schema inspection so it uses only metadata
• Refactor schemas in autoai_libs

0.7.3

1. Test-suite improvements such as adding sphinx build
2. Documentation improvements: fixed all sphinx warnings
3. New operators: TargetEncoder and fairSMOTE
4. Bug fixes and support of new schema features such as "transient":"alwaysPrint" to always print a hyperparameter value in pretty_print even if it has default value.

0.7.2

CI and RASL fixes.

0.7.1

• fixes to autogen schemas
• fix to autoai_libs DateTransformer

0.7.0

• Improves support for partial_fit
• Improves the pretty printer
• Improves support for typed users
• Adds lale.lib.sklearn.perceptron (wrapping sklearn.linear_model.Perceptron)
• RASL (experimental):
  • Removes support for Spark Dataframes that don't have an index
  • Moves HashingEncoder to category_encoders and improved documentation

0.6.19

Updated version of aif360 during installation.

0.6.16

Adding py.typed marker to enable MyPy on packages that use Lale.

0.6.17

1. fit_transform for lale operators
2. partial_fit for xgboost and lightgbm
3. Minor fixes and updates to README.