clean_column_names

Enhanced column name cleaning with better robustness

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

clean_column_names function

<dl><dt>names</dt>
<dd>Character vector of column names</dd></dl>

Arguments

Enhanced column name cleaning with better robustness — clean_column_names

<dl>

<dt>names</dt>
<dd>Character vector of column names</dd>

</dl>

clean_column_names: Enhanced column name cleaning with better robustness

Description

Usage

Value

Arguments