You can figure out whether a given model engine supports sparse data by
calling get_encoding("name of model") and looking at the allow_sparse_x
column.
Details
Using sparse data for model fitting and prediction shouldn't require any
additional configurations. Just pass in a sparse matrix such as dgCMatrix
from the Matrix package or a sparse tibble from the sparsevctrs package
to the data argument of fit(), fit_xy(), and predict().
Models that don't support sparse data will try to convert to non-sparse data with warnings. If conversion isn’t possible, an informative error will be thrown.