specified_masks_mask_generator: A 'torch::nn_module()' Representing a...
In shapr: Prediction Explanation with Dependence-Aware Shapley Values

View source: R/approach_vaeac_torch_modules.R

specified_masks_mask_generator

R Documentation

A `torch::nn_module()` Representing a specified_masks_mask_generator

Description

A mask generator which masks the entries based on sampling provided 1D masks with corresponding probabilities. Used for Shapley value estimation when only a subset of coalitions are used to compute the Shapley values.

Usage

specified_masks_mask_generator(masks, masks_probs, paired_sampling = FALSE)

Arguments

`masks`	Matrix/Tensor of possible/allowed 'masks' which we sample from.
`masks_probs`	Array of 'probabilities' for each of the masks specified in 'masks'. Note that they do not need to be between 0 and 1 (e.g. sampling frequency). They are scaled, hence, they only need to be positive.
`paired_sampling`	Boolean. If we are doing paired sampling. So include both S and `\bar{S}`. If TRUE, then batch must be sampled using 'paired_sampler' which creates batches where the first half and second half of the rows are duplicates of each other. That is, `⁠batch = [row1, row1, row2, row2, row3, row3, ...]⁠`.