Releases: JuliaAI/MLJEnsembles.jl
Releases · JuliaAI/MLJEnsembles.jl
v0.4.3
v0.4.2
MLJEnsembles v0.4.2
Merged pull requests:
v0.4.1
v0.4.0
MLJEnsembles v0.4.0
- (breaking) Remove MLJBase as dependency, replacing it with StatisticalMeasuresBase.jl. Adapt code appropriately to the new measures API. To use MLJEnsembles.jl without MLJBase.jl, one may need to explicitly import StatisticalMeasures.jl. See also the MLJBase 1.0 migration guide for further details (#30).
Merged pull requests:
v0.3.3
v0.3.2
v0.3.1
v0.3.0
MLJEnsembles v0.3.0
- (enhancement, breaking) Adapt to MLJBase 0.20, and in particular the new serialization API, which allows serialisation of
EnsembleModel(model=...)
wheremodel
is not necessarily a pure-Julia model (#15) @olivierlabayle - (bug fix) Enable safe wrapping of atomic models that implement a data front-end (#17) @OkonSamuel
Closed issues:
- Ensembling fails for atomic models implementing the
reformat
/selectrows
interface for caching model specific data representations (#16)
Merged pull requests:
- add serialization of ensembles (#15) (@olivierlabayle)
- fix data front-end bug #16 (#17) (@OkonSamuel)
- For a 0.3.0 release (#18) (@ablaom)
v0.2.0
MLJEnsembles v0.2.0
- (breaking) Change syntax
EnsembleModel(atom=...)
toEnsembleModel(model=...)
for consistency with other MLJ model wrappers (eg,TunedModel
) but additionally allow passing model as non-keyword argument, as inEnsembleModel(my_tree, ...)
. - Add CategoricalDistributions.jl as a dependency
- Bump compat for MLJBase to 0.19 and address the fact that UnivariateFinite functionality is not defined in MLJBase 0.19, but in CategoricalDistributions.jl instead.
Merged pull requests: