vaeac_get_mask_generator_name function

Function that determines which mask generator to use

vaeac_get_mask_generator_name(
  mask_gen_coalitions,
  mask_gen_coalitions_prob,
  masking_ratio,
  verbose
)

Arguments

• mask_gen_coalitions: Matrix (default is NULL). Matrix containing the coalitions that the vaeac model will be trained on, see specified_masks_mask_generator(). This parameter is used internally in shapr when we only consider a subset of coalitions, i.e., when n_coalitions $< 2^{n_{\text{features}}}$, and for group Shapley, i.e., when group is specified in explain().

• mask_gen_coalitions_prob: Numeric array (default is NULL). Array of length equal to the height of mask_gen_coalitions containing the probabilities of sampling the corresponding coalitions in mask_gen_coalitions.

• masking_ratio: Numeric (default is 0.5). Probability of masking a feature in the mcar_mask_generator() (MCAR = Missing Completely At Random). The MCAR masking scheme ensures that vaeac

  model can do arbitrary conditioning as all coalitions will be trained. masking_ratio will be overruled if mask_gen_coalitions is specified.

• verbose: String vector or NULL. Specifies the verbosity (printout detail level) through one or more of strings "basic", "progress", "convergence", "shapley" and "vS_details". "basic" (default) displays basic information about the computation which is being performed. "progress displays information about where in the calculation process the function currently is. #' "convergence" displays information on how close to convergence the Shapley value estimates are (only when iterative = TRUE) . "shapley" displays intermediate Shapley value estimates and standard deviations (only when iterative = TRUE)

  • the final estimates. "vS_details" displays information about the v_S estimates. This is most relevant for approach %in% c("regression_separate", "regression_surrogate", "vaeac"). NULL means no printout. Note that any combination of four strings can be used. E.g. verbose = c("basic", "vS_details") will display basic information + details about the v(S)-estimation process.

Returns

The function does not return anything.

Author(s)

Lars Henry Berge Olsen