Abstract: Feature selection is a cornerstone in advancing the accuracy and efficiency of predictive models, particularly in nuanced domains like socio-economic analysis. This study explores nine ...

Abstract: Multi-label feature selection solves the high-dimensional challenge problem in multi-label learning, and is widely used in pattern recognition, machine learning, and other related fields.

Multi-Criteria Decision Making (MCDM) in site selection brings together quantitative and qualitative factors to identify optimal locations for facilities ranging from emergency services to retail ...