Computes G1 score from a confusion matrix, see confusion. G1 score is F1 score with
reversed roles of 0/1 classifications, see Petersen et al. 2022.
The G1 score is defined as \(2 * TN/(2 * TN + FN + FP)\), where TN are true negatives,
FP are false positives, and FN are false negatives. If TN + FN + FP = 0, 1 is returned.

Various tools for inferring causal models from observational data. The package
includes an implementation of the temporal Peter-Clark (TPC) algorithm. Petersen, Osler
and Ekstrøm (2021) <doi:10.1093/aje/kwab087>. It also includes general tools
for evaluating differences in adjacency matrices, which can be used for evaluating
performance of causal discovery procedures.

Bjarke Hautop Kristensen

causalDisco

Tools for Causal Discovery on Observational Data

Anne Helby Petersen

Tobias Ellegaard Larsen

Claus Thorn Ekstrøm

G1 function

<dl><dt>confusion</dt>
<dd>Confusion matrix as obtained from confusion</dd></dl>

Arguments

G1 score — G1

<dl>

<dt>confusion</dt>
<dd>Confusion matrix as obtained from confusion</dd>

</dl>

G1: G1 score

Description

Usage

Value

Arguments

References