regression.surrogate_aug_data: Augment the training data and the explicands

Description

Augment the training data and the explicands

Usage

regression.surrogate_aug_data(
  internal,
  x,
  y_hat = NULL,
  index_features = NULL,
  augment_masks_as_factor = FALSE,
  augment_include_grand = FALSE,
  augment_add_id_coal = FALSE,
  augment_comb_prob = NULL,
  augment_weights = NULL
)

Value

A data.table containing the augmented data.

Arguments

internal: List. Holds all parameters, data, functions and computed objects used within explain() The list contains one or more of the elements parameters, data, objects, iter_list, timing_list, main_timing_list, output, and iter_timing_list.
x: Data.table containing the training data.
y_hat: Vector of numerics (optional) containing the predicted responses for the observations in x.
index_features: Array of integers (optional) containing which coalitions to consider. Must be provided if x is the explicands.
augment_masks_as_factor: Logical (default is FALSE). If TRUE, then the binary masks are converted to factors. If FALSE, then the binary masks are numerics.
augment_include_grand: Logical (default is FALSE). If TRUE, then the grand coalition is included. If index_features are provided, then augment_include_grand has no effect. Note that if we sample the coalitions then the grand coalition is equally likely to be samples as the other coalitions (or weighted if augment_comb_prob is provided).
augment_add_id_coal: Logical (default is FALSE). If TRUE, an additional column is adding containing which coalition was applied.
augment_comb_prob: Array of numerics (default is NULL). The length of the array must match the number of coalitions being considered, where each entry specifies the probability of sampling the corresponding coalition. This is useful if we want to generate more training data for some specific coalitions. One possible choice would be augment_comb_prob = if (use_Shapley_weights) internal$objects$X$shapley_weight[2:actual_n_coalitions] else NULL.
augment_weights: String (optional). Specifying which type of weights to add to the observations. If NULL (default), then no weights are added. If "Shapley", then the Shapley weights for the different coalitions are added to corresponding observations where the coalitions was applied. If uniform, then all observations get an equal weight of one.

Author

Lars Henry Berge Olsen