sparse_data: Using sparse data with recipes

In tidymodels/recipes: Preprocessing and Feature Engineering Steps for Modeling

Using sparse data with recipes

Description

recipe(), prep(), and bake() all accept sparse tibbles from the sparsevctrs package and sparse matrices from the Matrix package. Sparse matrices are converted to sparse tibbles internally as each step expects a tibble as its input, and is expected to return a tibble as well.

Details

Several steps work with sparse data. A step can either work with sparse data, ruin sparsity, or create sparsity. The documentation for each step will indicate whether it will work with sparse data or create sparse columns. If nothing is listed it is assumed to ruin sparsity.

Sparse tibbles or data.frames will be returned from bake() if sparse columns are present in data, either from being generated in steps or because sparse data was passed into recipe(), prep(), or bake().

tidymodels/recipes documentation built on Nov. 29, 2024, 3:05 p.m.