Version 0.9.4

Update lale version to 0.9.4

• Support Pandas 3.X
• Support xgboost up to 3.3.X
• Doc updates: Persian translation of README and Snap ML examples
  • Thanks @AmirhosseinHonardoust !
• Modernize and update setup / pyproject.toml / linters

Signed-off-by: Avi Shinnar shinnar@us.ibm.com

Version 0.9.3

• Support newer versions of snapml
• Hyperopt compatibility fixes
  • Add upper bounds to setuptools
  • Workaround for hyperopt.anneal strategy
• Fix tests
  • Accomodate minor changes in orbis output
  • Disable testing newop tutorial notebook due to trouble downloading the dataset
• Tooling improvements
  • Update pyright version
  • Update github actions versions

Version 0.9.2

Add basic pyproject.toml

Dependency updates:

• Add support for scikit-learn 1.7
• Increase upper bound on jsonschema
• Remove astunparse

Version 0.9.1

Dependency updates:

• Make graphviz dependency optional
• Increase upper bound on jsonschema
• Upper bound pyspark dependency to < 4.0
• Support newer versions of numpy
• Add autoai-fairness dependency set with appropriate version bounds on depdendencies

Dependency Update Release

Maintenance release that supports newer versions of dependencies.

• Add support for Python 3.12
• Add support for Numpy>=2.0
• Support newer versions of dependencies:
  • imbalanced-learn: 0.13
  • XGBoost: 3.0
  • lightgbm: 4.6
  • SnapML: 1.16
  • scikit-learn: 1.6
• Improvements to test datasets
  • Replace use of no longer available dataset
  • Enable support for prefetching and caching datasets in CI
• Update all static tools

Removals/Known Issues:

• Remove support for Python 3.8 and Python 3.9
  • Python 3.9 is still believed to work , but it is no longer tested as part of CI and hence no longer supported.
• Disable testing for RASL subsystem.
  • It should still work with older versions of Numpy and Python, however it currently breaks with newer versions
  • This breakage will hopefully be fixed, and tests re-enabled, in a future release.
• Testing now generally happens against Numpy>=2.0. Numpy 1.X should still work, however it is no longer well-tested or supported.

Version 0.8.4

Adds support for hyperopt 0.2.7

Version 0.8.3

• Visualizations as SVG with links and tooltips in jupyter notebook >=7.
• Eliminated dependency on numpy<2 directly in Lale, but note that some packages that are used with Lale still depend on numpy<2.

Version 0.8.2

• Improvements to the release deployment scripts

Version 0.8.1

This release includes minor bug fixes

• Fix for xgb classifier without a label encoder
• URL links fix to open them in new tab
• Use newer AIF360 version that does not require an upper bound on numpy version

Version 0.8.0

• Add support for Python 3.11
  • The SMAC hyperoptimization backend is not currently supported on 3.11
• Add support for scikit-learn 1.3 and 1.4
• Update supported versions of numpy, scipy, pandas, xgboost, lightgbm, snapml, and tensorflow
  • AIF360 does not currently support numpy>=1.24, so testing for aif360 libraries is done using an older version of numpy
• Fix readthedocs build so our documentation is correctly updated
• Add label encoding to our wrapper for XGBClassifier, since it longer does this.
• Shuffle data in some batching tests to (mostly) avoid problems with encoding
• Remove support for Python 3.7 and scikit-learn < 1.0
• Remove autoai_libs wrappers and tests (they have been moved into the autoai_libs package).