NEWS

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caretEnsemble 4.0.1 (2024-09-12)

• Speed up the example for autoplot so it runs in <1 second on most platforms

caretEnsemble 4.0.0 (2024-08-17)

• 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 (2023-09-20)

• Fix broken package documentation with new roxygen2
• Replace deprecated linters with the new versions

caretEnsemble 2.0.2 (2023-02-09)

• Fix broken tests on r-devel

caretEnsemble 2.0.1 (2019-12-12)

• Minor fixes to support R 4.0

caretEnsemble 2.0.0 (2016-02-07)

• 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

• caretEnsemble is a new package for making ensembles of caret models.