create_coalition_table: Define coalitions, and fetch additional information about...
In shapr: Prediction Explanation with Dependence-Aware Shapley Values

create_coalition_table

R Documentation

Define coalitions, and fetch additional information about each unique coalition

Description

Define coalitions, and fetch additional information about each unique coalition

Usage

create_coalition_table(
  m,
  exact = TRUE,
  n_coalitions = 200,
  weight_zero_m = 10^6,
  paired_shap_sampling = TRUE,
  prev_coal_samples = NULL,
  prev_coal_samples_n_unique = NULL,
  n_samps_scale = 10,
  coal_feature_list = as.list(seq_len(m)),
  approach0 = "gaussian",
  kernelSHAP_reweighting = "none",
  dt_valid_causal_coalitions = NULL
)

Arguments

`m`	Positive integer. Total number of features/groups.
`exact`	Logical. If `TRUE` all `2^m` coalitions are generated, otherwise a subsample of the coalitions is used.
`n_coalitions`	Positive integer. Note that if `exact = TRUE`, `n_coalitions` is ignored.
`weight_zero_m`	Numeric. The value to use as a replacement for infinite coalition weights when doing numerical operations.
`paired_shap_sampling`	Logical. Whether to do paired sampling of coalitions.
`prev_coal_samples`	Character vector. A vector of previously sampled coalitions as characters. Each string contains a coalition and the feature indices in the coalition is separated by a space. For example, "1 5 8" is a coalition with features 1, 5, and 8.
`prev_coal_samples_n_unique`	Positive integer. The number of unique coalitions in `prev_coal_samples`. This is a separate argument to avoid recomputing the number unnecessarily.
`n_samps_scale`	Positive integer. Integer that scales the number of coalitions `n_coalitions` to sample as sampling is cheap, while checking for `n_coalitions` unique coalitions is expensive, thus we over sample the number of coalitions by a factor of `n_samps_scale` and determine when we have `n_coalitions` unique coalitions and only use the coalitions up to this point and throw away the remaining coalitions.
`coal_feature_list`	List. A list mapping each coalition to the features it contains.
`approach0`	Character vector. Contains the approach to be used for estimation of each coalition size. Same as `approach` in `explain()`.
`dt_valid_causal_coalitions`	data.table. Only applicable for asymmetric Shapley values explanations, and is `NULL` for symmetric Shapley values. The data.table contains information about the coalitions that respects the causal ordering.