feature_matrix_cpp

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 Løland (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

Annabelle Redelmeier

Anders Løland

Jens Christian Wahl

Camilla Lingjærde

Norsk Regnesentral 

feature_matrix_cpp function

<dl><dt>features</dt>
<dd>List</dd>
<dt>m</dt>
<dd>Positive integer. Total number of features</dd></dl>

Arguments

Author

Get feature matrix — feature_matrix_cpp

<dl>

<dt>features</dt>
<dd>List</dd>


<dt>m</dt>
<dd>Positive integer. Total number of features</dd>

</dl>

Get feature matrix

feature_matrix_cpp: Get feature matrix

Description

Usage

Value

Arguments

Author