preprocess_imported_data

A preprocessing function to handle common data issues, such as removing empty rows/columns, handling dates, and converting character columns to factors. This function improves data quality before further analysis.

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

preprocess_imported_data function

<dl><dt>data</dt>
<dd>Input data.frame to be preprocessed.</dd>
<dt>preprocessing</dt>
<dd>A list of preprocessing options, such as removing empty rows or handling dates.</dd>
<dt>verbose</dt>
<dd>Logical flag indicating whether to show progress messages (default is FALSE).</dd></dl>

Arguments

Enhanced preprocessing with better performance and robustness — preprocess_imported_data

<dl>

<dt>data</dt>
<dd>Input data.frame to be preprocessed.</dd>


<dt>preprocessing</dt>
<dd>A list of preprocessing options, such as removing empty rows or handling dates.</dd>


<dt>verbose</dt>
<dd>Logical flag indicating whether to show progress messages (default is FALSE).</dd>

</dl>

preprocess_imported_data: Enhanced preprocessing with better performance and robustness

Description

Usage

Value

Arguments