aicc_full_cpp

Numeric. Specifies the scaling (sigma)

X_list

mcov_list

Logical. Indicates whether Mahalanobis distance should be scaled with the
number of variables

S_scale_dist

y_list

negative

AICc formula for several sets, alternative definition

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

Nikolai Sellereite

Anders L<c3><b8>land

Jens Christian Wahl

Camilla Lingj<c3><a6>rde

Norsk Regnesentral 

aicc_full_cpp function

AICc formula for several sets, alternative definition — aicc_full_cpp

AICc formula for several sets, alternative definition

aicc_full_cpp: AICc formula for several sets, alternative definition

Description

Usage

Arguments

Value