The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
REPROPREP: Reproducible Preprocessing Validation Framework - A Systematic Framework for Preprocessing Validation in Business Analytics
|
|
Author(s): Miguel Angel Jimenez Garcia (Universidad Americana de Europa, Mexico)and Richard De Jesus Gil Herrera (Universidad Internacional de la Rioja, Spain)
Copyright: 2026
Volume: 13
Issue: 1
Pages: 26
Source title:
International Journal of Business Analytics (IJBAN)
Editor(s)-in-Chief: John Wang (Montclair State University, USA)
DOI: 10.4018/IJBAN.406288
Purchase
|
Abstract
Preprocessing strategy selection in business analytics typically relies on convention rather than systematic evidence, despite consuming 60–80% of project effort. This study introduces REPROPREP (v1.0), a methodological framework for validating preprocessing effectiveness assumptions through statistical analysis and cost-benefit assessment. The framework applies Benjamini-Hochberg false discovery rate correction, quality degradation protocols, and cost-effectiveness evaluation. A demonstration across 10 UCI datasets, three preprocessing strategies, and gradient boosting classifiers with 5-fold stratified cross-validation yielded no statistically significant performance differences after multiple comparisons correction (mean effect size: 0.001 AUC), with implementation cost differences ranging from $150–$800. Focused on numeric preprocessing, REPROPREP provides organizations with a rigorous, context-specific methodology for evaluating preprocessing assumptions. Generalizability requires validation beyond tested conditions. Reproducible code is publicly available.
Related Content
|
André Guimarães, Rosivalda Pereira, Maria Teresa Pereira, Afonso Carvalho, Pedro Reis, Antonio J. Marques Marques Cardoso.
© 2026.
17 pages.
|
|
Miguel Angel Jimenez Garcia, Richard De Jesus Gil Herrera.
© 2026.
26 pages.
|
|
María Belén Navarro, César Joel Ybañez, Gisela Analy Fernández Hurtado.
© 2026.
24 pages.
|
|
Shalina Sultana Champa, Richard S. Segall.
© 2026.
38 pages.
|
|
Muhammed Golec, Lifeng Zhu, Emir Sahin Hatay, Han Wang, Sukhpal Singh Gill.
© 2025.
26 pages.
|
|
Ahmet Alkan Çelik, Yavuz Selim Balcıoğlu, Erkut Altındağ.
© 2025.
14 pages.
|
|
Susana Álvarez-Díez, J. Samuel Baixauli-Soler, Anna Kondratenko.
© 2025.
25 pages.
|
|
|