determine_risk_level

Determine risk level and CSS class from severity counts.

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

determine_risk_level function

<dl><dt>severity_counts</dt>
<dd>Named integer vector of severity frequencies.</dd></dl>

Arguments

Determine risk level and CSS class from severity counts. — determine_risk_level

<dl>

<dt>severity_counts</dt>
<dd>Named integer vector of severity frequencies.</dd>

</dl>

determine_risk_level: Determine risk level and CSS class from severity counts.

Description

Usage

Value

Arguments