vaeac_compute_normalization: Compute Featurewise Means and Standard Deviations

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

Compute Featurewise Means and Standard Deviations

Description

Returns the means and standard deviations for all continuous features in the data set. Categorical features get mean = 0 and sd = 1 by default.

Usage

vaeac_compute_normalization(data, one_hot_max_sizes)

Arguments

data	A torch_tensor of dimension n_observation x n_features containing the data.
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.

Value

List containing the means and the standard deviations of the different features.

Author(s)

Lars Henry Berge Olsen

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