Review of Feature Selection Methods and Their Ensembles

Feature selection poses a common challenge in data mining and machine learning. This paper offers a comprehensive overview of the field, encompassing its historical context, recent advancements, and associated challenges. Topics covered include categorization of feature selection methods, development of ensemble frameworks, and assessment of selection stability. Current research trends in feature selection and computational intelligence are examined, alongside practical applications in ensemble configuration, threshold detection, evaluation criteria, and stability enhancement techniques. This article is categorized under: Algorithmic Development > Ensemble Methods