Runs all the solvers on (x, y) training data with SLOPE parameter alpha, prints the total time in each case, and returns the merged data frame.

Runs all the solvers on (x, y) training data with SLOPE parameter alpha, prints the total time in each case, and returns the merged data frame.

getBenchmarks(
  x,
  y,
  family = c("gaussian", "binomial", "multinomial", "poisson"),
  alpha = 0.01,
  path_length = 1
)

Arguments

x	the design matrix, which can be either a dense matrix of the standard matrix class, or a sparse matrix inheriting from Matrix::sparseMatrix. Data frames will be converted to matrices internally.
y	the response, which for family = "gaussian" must be numeric; for family = "binomial" or family = "multinomial", it can be a factor.
family	model family
alpha	parameter used for SLOPE regularization
path_length	The regularization path length. By default, it is one. 'alpha' is ignored if path_length is not 1, in which case, list of alpha and the length of the list is returned.