glum 3.0.0
MatthiasSchmidtblaicherQC
released this
27 Apr 17:34
·
59 commits
to main
since this release
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
exceptX
,y
,sample_weight
andoffset
are now keyword-only. - :class:
~glum.GeneralizedLinearRegressor
's default value foralpha
is now0
, 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 fromp
topower
, in line with :class:~glum.TweedieDistribution
. - :class:
~glum.TweedieLink
no longer instantiates :class:~glum.IdentityLink
or :class:~glum.LogLink
forpower=0
andpower=1
, respectively. On the other hand, :class:~glum.TweedieLink
is now compatible withpower=0
andpower=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.