Eleven quick tips to reduce overfitting in machine learning
Eleven practical tips for reducing unintentional overfitting in supervised biomedical machine learning studies are presented and stress principled data splitting, domain-informed preprocessing, controlled model complexity, systematic tuning, comprehensive performance evaluation, and robustness analysis.