inv_gaussian_transform

Numeric vector. The first <code>n_z</code> items are the Gaussian data, and the last part is
the data with the original transformation.

Positive integer. Number of elements of <code>zx</code> that belongs to new data.

Transforms new data to a standardized normal distribution

internal

Complex machine learning models are often hard to interpret. However, in
many situations it is crucial to understand and explain why a model made a specific
prediction. Shapley values is the only method for such prediction explanation framework
with a solid theoretical foundation. Previously known methods for estimating the Shapley
values do, however, assume feature independence. This package implements the method
described in Aas, Jullum and L<c3><b8>land (2019) <arXiv:1903.10464>, which accounts for any feature
dependence, and thereby produces more accurate estimates of the true Shapley values.

Martin Jullum

shapr

Prediction Explanation with Dependence-Aware Shapley Values

inv_gaussian_transform: Transforms new data to a standardized normal distribution

Description

Usage

Arguments

Value