e fold and not k fold (Green Recommender Systems)

From Theory to Practice: Implementing and Evaluating e-Fold Cross-Validation

Accepted for publication at the International Conference on Artificial Intelligence and Machine Learning Research (CAIMLR). The PDF is available here. Feel free to also read the original proposal that led to the current publication. Abstract In this paper, we present e-fold cross-validation, an energy-efficient alternative to k-fold, which dynamically adjusts Read more…

e-fold cross-validation: A computing and energy-efficient alternative to k-fold cross-validation with adaptive folds [Proposal]

This proposal is also available as pre-print (PDF) on OSF.io. If you want to cite this proposal, please cite: Introduction K-fold cross-validation is widely regarded as a robust method for model evaluation in machine learning and related fields, including recommender systems. Unlike a simple hold-out split, k-fold cross-validation ensures that Read more…