Enhancing Multi-Objective Machine Learning with an Optimized Lexicographic Approach: Determining the Tolerance Threshold - Fernandes, Guilherme G. D.; Medeiros, Talles H. (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC); 2024: Anais do XXI Encontro Nacional de Inteligência Artificial e ComputacionalDO - 10.5753/eniac.2024.245204, 2024)
Determining optimal tolerance in lexicographic multi-objective optimization is crucial for robust results. This paper introduces a machine learning algorithm that automatically sets the appropriate tolerance, optimizing the lexicographic strategy and enhancing the analysis of tolerance impact on outcomes. Applied to various datasets, our method consistently provides insights into the relationship between tolerance and model performance. Results show that automatic tolerance optimization improves computational efficiency and accuracy. These findings highlight the importance of addressing tolerance in multi-objective optimization.