precision

Computes precision (aka positive predictive value) from a confusion matrix,
see confusion.
Precision is defined as TP/(TP + FP), where TP are true positives and
FP are false positives. If TP + FP = 0, 0 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

precision function

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

Arguments

Precision — precision

<dl>

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

</dl>

precision: Precision

Description

Usage

Value

Arguments