glum 3.1.0

3.1.0 - 2024-11-11

New features:

• New argument max_inner_iter for classes GeneralizedLinearRegressor and GeneralizedLinearRegressorCV to control the maximum number of iterations of the inner solver in the IRLS-CD algorithm.
• New fitted attributes col_means_ and col_stds_ for classes GeneralizedLinearRegressor and GeneralizedLinearRegressorCV.
• GeneralizedLinearRegressor now prints more informative logs when fitting with alpha_search=True and verbose=True.

Bug fixes:

• Fixed a bug where GeneralizedLinearRegressor.fit would raise a dtype mismatch error if fit with alpha_search=True.
• Use data type (float64 or float32) dependent precision in solvers.

glum 3.0.2

What's Changed

• Fix bug in Wald test with term names without intercept by @MatthiasSchmidtblaicherQC in #797
• Bump mamba-org/setup-micromamba from 1.8.1 to 1.9.0 by @dependabot in #798
• remove libblas mkl dependency by @MarcAntoineSchmidtQC in #799
• Use ruff as our linter and formatter by @MarcAntoineSchmidtQC in #800
• Pre-commit autoupdate by @quant-ranger in #803
• Combine parsing of initial values by @lbittarello in #805
• Support for build with numpy 2.0 by @MarcAntoineSchmidtQC in #809
• Bump pypa/cibuildwheel from 2.18.1 to 2.19.1 by @dependabot in #808
• Bump pypa/gh-action-pypi-publish from 1.8.14 to 1.9.0 by @dependabot in #807
• Switch to pixi by @stanmart in #802
• Prepare release 3.0.2 by @MarcAntoineSchmidtQC in #812

Full Changelog: 3.0.1...3.0.2

glum 3.0.1

Bug fix

• We now support scikit-learn 1.5.

glum 3.0.0

3.0.0 - 2024-04-27

Breaking changes:

• All arguments to :class:~glum.GeneralizedLinearRegressorBase, :class:~glum.GeneralizedLinearRegressor and :class:~glum.GeneralizedLinearRegressorCV are now keyword-only.
• All arguments to public methods of :class:~glum.GeneralizedLinearRegressorBase, :class:~glum.GeneralizedLinearRegressor or :class:~glum.GeneralizedLinearRegressorCV except X, y, sample_weight and offset are now keyword-only.
• :class:~glum.GeneralizedLinearRegressor's default value for alpha is now 0, i.e. no regularization.
• :class:~glum.GammaDistribution, :class:~glum.InverseGaussianDistribution, :class:~glum.NormalDistribution and :class:~glum.PoissonDistribution no longer inherit from :class:~glum.TweedieDistribution.
• The power parameter of :class:~glum.TweedieLink has been renamed from p to power, in line with :class:~glum.TweedieDistribution.
• :class:~glum.TweedieLink no longer instantiates :class:~glum.IdentityLink or :class:~glum.LogLink for power=0 and power=1, respectively. On the other hand, :class:~glum.TweedieLink is now compatible with power=0 and power=1.

New features:

• Added a formula interface for specifying models.
• Improved feature name handling. Feature names are now created for non-pandas input matrices too. Furthermore, the format of categorical features can be specified by the user.
• Term names are now stored in the model's attributes. This is useful for categorical features, where they refer to the whole variable, not just single levels.
• Added more options for treating missing values in categorical columns. They can either raise a ValueError ("fail"), be treated as all-zero indicators ("zero") or represented as a new category ("convert").
• meth:GeneralizedLinearRegressor.wald_test can now perform tests based on a formula string and term names.
• :class:~glum.InverseGaussianDistribution gains a :meth:~glum.InverseGaussianDistribution.log_likelihood method.

glum 2.7.0

2.7.0 - 2024-02-19

Bug fix:

• Added cython compiler directive legacy_implicit_noexcept = True to fix performance regression with cython 3.

Other changes:

• Require Python>=3.9 in line with NEP 29 <https://numpy.org/neps/nep-0029-deprecation_policy.html#support-table>.
• Build and test with Python 3.12 in CI.
• Added line search stopping criterion for tiny loss improvements based on gradient information.
• Added warnings about breaking changes in future versions.

glum 3.0.0a2

What's Changed

• Fix formula context by @MartinStancsicsQC in #691

Full Changelog: 3.0.0a1...3.0.0a2

glum 2.6.0

2.6.0 - 2023-09-05

New features:

• Added the complementary log-log (cloglog) link function.
• Added the option to store the covariance matrix after estimating it. In this case, the covariance matrix does not have to be recomputed when calling inference methods.
• Added methods for performing Wald tests based on a restriction matrix, feature names or term names.
• Added a method for creating a coefficient table with confidence intervals and p-values.

Bug fix:

• Fixed GeneralizedLinearRegressorBase.covariance_matrix mutating feature names when called with a data frame. See here.

Other changes:

• When computing the covariance matrix, check whether the design matrix is ill-conditioned for all types of input. Furthermore, do it in a more efficient way.
• Pin tabmat<4.0.0 (the new release will bring breaking changes).

glum 3.0.0a1

What's Changed

• Bump pypa/cibuildwheel from 2.14.1 to 2.15.0 by @dependabot in #680
• Column names à la Tabmat #278 by @MartinStancsicsQC in #678
• Pre-commit autoupdate by @quant-ranger in #685
• Bump mamba-org/setup-micromamba from 1.1.3 to 1.4.3 by @dependabot in #686
• Add methods for performing Wald-tests by @MartinStancsicsQC in #668
• Formula interface by @MartinStancsicsQC in #670
• Formula- and term-based Wald-tests by @MartinStancsicsQC in #689
• Support for missing values in categorical columns by @MartinStancsicsQC in #684

Full Changelog: v3.0.0a0...3.0.0a1

glum 3.0.0a0

3.0.0a0 - 2023-08-17

Main change

• Ensure glum's compatibility with the new major release of tabmat (version 4.0.0) by @MartinStancsicsQC

Note that glum 3 is not compatible with pre-4.0.0 versions of tabmat.

Full Changelog: 2.5.2...v3.0.0a0

glum 2.5.2

2.5.2 - 2023-06-02

Bug fix

• Fixed a bug in glum.GeneralizedLinearRegressor when fit on a data set with a constant column and warm_start=True. See #645.

Other changes:

• We now pin llvm-openmp=11 when creating the wheel for macOS in line with scikit-learn. This should prevent segfaults on macOS with Intel architecture.
• Fixed a bug in the glm_benchmarks_analyze command line tool. See #642.
• Remove dev dependency on dask_ml.