Version 0.5.0

v0.5.0 - 2023-12-13

Added

• added support for AVX-512 in PyPI installations to improve fitting speed
• introduced an option to disable SIMD optimizations through the debug_mode function in python
• exposed public utils.link_func and utils.inv_link functions

Changed

• the interpret-core package now installs the dependencies required to build and predict EBMs
  by default without needing to specify the [required] pip install flag
• experimental/private support for OVR multiclass EBMs
• added bagged_intercept_ attribute to store the intercepts for the bagged models

Fixed

• resolved an issue in merge_ebms where the merge would fail if all EBMs in the
  merge contained features with only one bin (issue #485)
• resolved multiple future warnings from other packages

Breaking Changes

• changed how monoclassification (degenerate classification with 1 class) is expressed
• replaced predict_and_contrib function with simpler eval_terms function that returns
  only the per-term contribution values. If you need both the contributions and predictions use:
  interpret.utils.inv_link(ebm.eval_terms(X).sum(axis=1) + ebm.intercept_, ebm.link_)
• separate to_json into to_jsonable (for python objects) and to_json (for files) functions
• create a new link function string for multiclass that is separate from binary classification
• for better scikit-learn compliance, removed the decision_function from the ExplainableBoostingRegressor