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NEWS
caretEnsemble 4.0.0
- Multiclass support! caretList, caretStack, and caretEnsemble
- The greedy optimizer is back! caretEnsemble now uses a greedy
optimizer by default. This optimizer can never be worse than the worst
single model. caretStack still support all caret models, including
glm.
- Refactored some internals for scalability (e.g. data.table for
predictions, trim some un-needed data by default).
- Moved all the S3 methods to caretStack, which now supports print,
summary, plot, dotplot, and autoplot. caretEnsemble inherits from
caretStack, and therefore also supports all of these methods.
- Allow ensembling of mixed lists of classification and regression
models.
- Allow ensemble of models with different resampling strategies, so
long as they were trained on the same data.
- Allow transfer learning for ensembling models trained on different
datasets.
- Added permutation importance as the default importance method for
caretLists and caretStacks.
- Add a default trainControl constructor to make it easier to build
good controls for training caretLists for stacking with caretStack.
- Expanded test coverage to 100%.
- Sped up test suite (unit tests now run in 20 seconds).
- Delinted codebase: now conforms with all available linters save the
object name linter.
- Added a makefile for easier local package development.
- Fixed badges in the readme.
- Added a pkgdown site.
- Switched to github actions (from travis) for CI.
- Internal refactoring, optimization, and bug fixes.
caretEnsemble 2.0.3
- Fix broken package documentation with new roxygen2
- Replace deprecated linters with the new versions
caretEnsemble 2.0.2
- Fix broken tests on r-devel
caretEnsemble 2.0.1
- Minor fixes to support R 4.0
caretEnsemble 2.0.0
- caretEnsemble now inherits from caretStack
- Removed the optimizers and now use a glm for caretEnsemble
(optimizers will be added back as caret.train models in a future
release)
- Cleaned up namespace (all dependencies are explicit imports, rather
than implicit imports or dependencies)
- Removed S3 functions that are not really S3 functions (e.g. autoplot
and fortify). We will either make those true S3 classes, or inherit from
the packages that define them in a future release
- Fixed the build on travis and locally
caretEnsemble 1.0.5
- Change output for predict functions to better align with other
predict methods in R (predict.caretEnsemble and predict.caretStack)
- Update documentation for predict methods to better explain the model
disagreement calculation
- Speed and memory improvements by switching to data.table for some
internals
- Modified the formula for a weighted standard deviation in the model
disagreement calculation
caretEnsemble 1.0 -
First CRAN release
- caretEnsemble is a new package for making ensembles of caret models.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.