Performs cross-validation for mixomics sPLS to select optimal keepX and keepY

Peforms cross-validation to assess the optimal number of features to retain in each dataset for a sPLS run (implemented in the mixOmics package).

Usage

spls_tune(
  spls_input,
  keepX = NULL,
  keepY = NULL,
  cpus = NULL,
  seed = NULL,
  ...
)

Arguments

spls_input: A mixOmics input object created with get_input_mixomics_unsupervised().
keepX: Numeric vector, values for the number of features to retain from dataset X to test. Default value is NULL (default sequence of values will be used, see details).
keepY: Numeric vector, values for the number of features to retain from dataset Y to test. Default value is NULL (default sequence of values will be used, see details).
cpus: Integer, the number of CPUs to use when running the code in parallel. For advanced users, see the BPPARAM argument of mixOmics::tune.spls().
seed: Integer, seed to use. Default is NULL, i.e. no seed is set inside the function.
...: Further arguments passed to mixOmics::tune.spls().

Value

A list (see mixOmics::tune.spls()).

Details

If no value is provided for keepX or keepY, the sequence seq(5, 30, 5) will be used, truncated to only retain values that are inferior or equal to the number of features in the X or Y dataset.