print.borg_cv_report

Automatically detects and enforces valid model evaluation by identifying
information reuse between training and evaluation data. Guards against data leakage,
look-ahead bias, and invalid cross-validation schemes that inflate performance estimates.
Supports temporal, spatial, and grouped evaluation structures.
Based on evaluation principles described in
Roberts et al. (2017) <doi:10.1111/ecog.02881>,
Kaufman et al. (2012) <doi:10.1145/2382577.2382579>, and
Kapoor & Narayanan (2023) <doi:10.1016/j.patter.2023.100804>.

Gilles Colling

BORG

Bounded Outcome Risk Guard for Model Evaluation

print.borg_cv_report function

<dl><dt>x</dt>
<dd>A borg_cv_report object.</dd>
<dt>...</dt>
<dd>Additional arguments (ignored).</dd></dl>

Arguments

Print CV Leakage Report — print.borg_cv_report

<dl>

<dt>x</dt>
<dd>A borg_cv_report object.</dd>


<dt>...</dt>
<dd>Additional arguments (ignored).</dd>

</dl>

print.borg_cv_report: Print CV Leakage Report

Description

Usage

Value

Arguments