How to overfit
Year: 2025
Type: article
Abstract: Overfitting remains a central challenge in modern data science, particularly as complex analytical tools become more accessible and widely applied in fields like chemometrics. This communication outlines a series of common pitfalls that lead to misleading and non-generalizable models – ranging from poor data quality and insufficient sample sizes to misuse of validation strategies and overly complex modeling choices. By illustrating a caricatured protocol for generating bad models, the paper emphasizes the importance of domain knowledge, appropriate experimental design, and rigorous validation. It advocates for "validity by design" as a proactive strategy to ensure robust, interpretable, and scientifically sound results.
Author: Rasmus Bro
Institution: University of Copenhagen
Language: English
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,970
OpenAlex ID: W4411202115