rss_cpp

Matrix. Output from <code><a rd-options="" href="/link/hat_matrix_cpp?package=shapr&version=0.1.3" data-mini-rdoc="shapr::hat_matrix_cpp">hat_matrix_cpp</a></code>

Vector, i.e. representing the response variable

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 

rss_cpp function

Matrix. Output from <code><a rd-options='' href='hat_matrix_cpp'>hat_matrix_cpp</a></code>

rss_cpp: sigma_hat_sq-function

Description

Usage

Arguments

Value