Cross-validation for training and testing co-occurrence network inference algorithms
Daniel Agyapong, Jeffrey Ryan Propster, Jane Marks, and 1 more author
BMC Bioinformatics, 2025
Cross-validation is a fundamental technique for evaluating machine learning models, but its application to co-occurrence network inference algorithms presents unique challenges. This work presents a comprehensive framework for applying cross-validation methods to assess the performance of algorithms that infer associations between biological entities from co-occurrence data.