print.leakr_report

internal

Provides utilities to detect common data leakage patterns including train/test
contamination, temporal leakage, and data duplication, enhancing model reliability and
reproducibility in machine learning workflows. Generates diagnostic reports and visual
summaries to support data validation. Methods based on best practices from Hastie,
Tibshirani, and Friedman (2009, ISBN:978-0387848570).

Cheryl Isabella

leakr

Data Leakage Detection Tools for Machine Learning

print.leakr_report function

<dl><dt>x</dt>
<dd>leakr_report object</dd>
<dt>...</dt>
<dd>TODO: Add description</dd></dl>

Arguments

Print method for leakr_report — print.leakr_report

<dl>

<dt>x</dt>
<dd>leakr_report object</dd>


<dt>...</dt>
<dd>TODO: Add description</dd>

</dl>

print.leakr_report: Print method for leakr_report

Description

Usage

Arguments