export_data_internal

Export data with consistent messaging

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

export_data_internal function

<dl><dt>data</dt>
<dd>Data.frame to export</dd>
<dt>file_path</dt>
<dd>Output file path</dd>
<dt>format</dt>
<dd>Output format</dd>
<dt>verbose</dt>
<dd>Whether to show messages</dd>
<dt>...</dt>
<dd>TODO: Add description</dd></dl>

Arguments

Export data with consistent messaging — export_data_internal

<dl>

<dt>data</dt>
<dd>Data.frame to export</dd>


<dt>file_path</dt>
<dd>Output file path</dd>


<dt>format</dt>
<dd>Output format</dd>


<dt>verbose</dt>
<dd>Whether to show messages</dd>


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

</dl>

export_data_internal: Export data with consistent messaging

Description

Usage

Value

Arguments