new_temporal_detector

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

new_temporal_detector function

<dl><dt>time_col</dt>
<dd>Character. Name of the time column</dd>
<dt>lookahead_window</dt>
<dd>Numeric. Lookahead window size (default 1)
Create a new temporal detector</dd></dl>

Arguments

Create a new temporal detector — new_temporal_detector

<dl>

<dt>time_col</dt>
<dd>Character. Name of the time column</dd>


<dt>lookahead_window</dt>
<dd>Numeric. Lookahead window size (default 1)
Create a new temporal detector</dd>

</dl>

new_temporal_detector: Create a new temporal detector

Description

Usage

Value

Arguments