2 papers
cs.LG2025
Beyond Random Sampling: Instance Quality-Based Data Partitioning via Item Response Theory
Lucas Cardoso, Vitor Santos, José Ribeiro Filho +3
Robust validation of Machine Learning (ML) models is essential, but traditional data partitioning approaches often ignore the intrinsic quality of each instance. This study propose…
cs.LG2025
Enhancing Classifier Evaluation: A Fairer Benchmarking Strategy Based on Ability and Robustness
Lucas Cardoso, Vitor Santos, José Ribeiro +3
Benchmarking is a fundamental practice in machine learning (ML) for comparing the performance of classification algorithms. However, traditional evaluation methods often overlook a…