Optimal Feature

Optimal feature selection aims to identify the most informative subset of features from a larger dataset, improving model performance and efficiency while reducing computational costs. Current research focuses on developing efficient algorithms, such as compact NSGA-II and adaptive query models, for multi-objective optimization and incorporating fairness constraints. These advancements are impacting diverse fields, from bioacoustics (animal sound classification) and image retrieval to medical diagnostics and resource management, by enhancing the accuracy and interpretability of machine learning models.