sample_combinations: Helper function to sample a combination of training and...

In shapr: Prediction Explanation with Dependence-Aware Shapley Values

Helper function to sample a combination of training and testing rows, which does not risk getting the same observation twice. Need to improve this help file.

Description

Helper function to sample a combination of training and testing rows, which does not risk getting the same observation twice. Need to improve this help file.

Usage

sample_combinations(ntrain, ntest, nsamples, joint_sampling = TRUE)

Arguments

ntrain	Positive integer. Number of training observations to sample from.
ntest	Positive integer. Number of test observations to sample from.
nsamples	Positive integer. Number of samples.
joint_sampling	Logical. Indicates whether train- and test data should be sampled separately or in a joint sampling space. If they are sampled separately (which typically would be used when optimizing more than one distribution at once) we sample with replacement if nsamples > ntrain. Note that this solution is not optimal. Be careful if you're doing optimization over every test observation when nsamples > ntrain.

Value

data.frame

Author(s)

Martin Jullum

shapr documentation built on May 4, 2023, 5:10 p.m.