gauss_cat_sampler_random: A 'torch::nn_module()' Representing a...

In NorskRegnesentral/shapr: Prediction Explanation with Dependence-Aware Shapley Values

A torch::nn_module() Representing a gauss_cat_sampler_random

Description

The gauss_cat_sampler_random generates random samples from the generative distribution defined by the output of the vaeac. The random sample is generated by sampling from the inferred Gaussian and categorical distributions for the continuous and categorical features, respectively.

Usage

gauss_cat_sampler_random(
  one_hot_max_sizes,
  min_sigma = 1e-04,
  min_prob = 1e-04
)

Arguments

one_hot_max_sizes	A torch tensor of dimension n_features containing the one hot sizes of the n_features features. That is, if the ith feature is a categorical feature with 5 levels, then one_hot_max_sizes[i] = 5. While the size for continuous features can either be 0 or 1.
min_sigma	For stability it might be desirable that the minimal sigma is not too close to zero.
min_prob	For stability it might be desirable that the minimal probability is not too close to zero.

Author(s)

Lars Henry Berge Olsen

NorskRegnesentral/shapr documentation built on April 19, 2024, 1:19 p.m.