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Releases: burning-cost/insurance-gam

v0.5.0

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@burning-cost burning-cost released this 03 Apr 17:20

New features

  • EBMInsuranceWrapper: actuarial facade for InterpretML EBM with balance checks, calibration diagnostics, and relativity extraction — replaces raw EBM usage with an interface designed around insurance pricing workflows (v0.2.0)
  • PostSelectionGLM: post-selection inference for Poisson GLMs, correcting for the bias introduced by variable selection before fitting
  • DebiasedGLM: bias-corrected confidence intervals for Lasso-selected GLM coefficients using debiasing via the score equation
  • PenalizedGLMInference: fit-once, explore-both interface combining penalised estimation with valid post-selection CIs — avoids refitting when switching between confidence interval methods
  • freMTPL2 external dataset benchmark comparing EBM against GLM and GBM baselines

Improvements

  • 165+ new tests across GLM inference modules, bringing the suite to comprehensive coverage of penalised and post-selection paths
  • EBM docstrings rewritten: Raises sections, typed returns, and prose descriptions of actuarial assumptions
  • References section added covering Hastie & Tibshirani (1990), Nori et al. (2019), and NAM literature
  • Databricks-format quickstart notebook committed to notebooks/
  • CI via GitHub Actions (Python 3.11+); numpy floor raised to >=2.0

Bug fixes

  • Fixed EBM offset handling for Poisson exposure
  • Resolved CI collection failure caused by missing torch in tests.yml
  • Corrected pl.Utf8 deprecation (renamed to pl.String in Polars >=0.19)
  • Bumped numpy minimum to >=1.25 for numpy.exceptions compatibility

v0.1.8

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@burning-cost burning-cost released this 23 Mar 04:52

Fix numpy minimum version to >=1.25 for numpy.exceptions compatibility

v0.1.6

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@burning-cost burning-cost released this 21 Mar 16:14

What's Changed

  • Added helpful ImportError messages for missing optional extras (ebm, anam, pin subpackages) so users get clear install guidance instead of cryptic ModuleNotFoundError
  • Fixed Tweedie objective to pass variance_power parameter correctly
  • Removed driver_age from monotone-increasing constraints (U-shaped relationship, not monotone)
  • Fixed score() docstring to clarify units of y
  • Added Python 3.13 to test matrix
  • Closed 5 Dependabot security alerts via transitive dep pins (werkzeug, flask, pyasn1)
  • Added pdoc API documentation with GitHub Pages deployment

Full Changelog: https://github.com/burning-cost/insurance-gam/compare/v0.1.6