On the tension between documenting R packages exhaustively and maintainably.
Weighing the pros and cons of several possible schemas for naming the core functions in {stacks}.
Why {stacks} requires (at least) four separate functions to build an ensemble model rather than wrapping them all up into one.
Introducing a set of blog posts reflecting on the development process of the {stacks} package.
Introducing ensemble learning to the tidymodels.
Model stacking is an ensembling technique that involves training a model to combine the outputs of many diverse statistical models. The stacks package implements a grammar for tidymodels-aligned model stacking.