Get table with sampled coalitions
sample_coalition_table(
m,
n_coalitions = 200,
weight_zero_m = 10^6,
paired_shap_sampling = TRUE,
prev_coal_samples = NULL,
prev_coal_samples_n_unique = NULL,
kernelSHAP_reweighting,
n_samps_scale = 10,
dt_valid_causal_coalitions = NULL
)Positive integer. Total number of features/groups.
Positive integer.
Note that if exact = TRUE, n_coalitions is ignored.
Numeric. The value to use as a replacement for infinite coalition weights when doing numerical operations.
Logical. Whether to do paired sampling of coalitions.
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.
Positive integer.
The number of unique coalitions in prev_coal_samples.
This is a separate argument to avoid recomputing the number unnecessarily.
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.
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.