The fuzzy sets and rough approach presented here open a new frontier for continued research and development Computational Intelligence and Feature Selection provides the reader with the background and fundamental ideas behind feature selection (FS), with an emphasis on techniques based on rough sets and fuzzy. Building on this foundation, this book provides: A critical review of the FS method, with special emphasis on the limitations of their current Program files implementing major algorithms, along with necessary instructions and datasets, available on Web sites related Coverage of the background and basic ideas behind FS A systematic presentation of leading methods are reviewed in a consistent algorithmic framework Real-world applications with working examples that illustrate the power and efficacy of FS closed approach FS investigations related areas, including rule induction and clustering of hybridizations using fuzzy and rough set theory Computational Intelligence and Feature Selection are an ideal resource for advanced scholars, graduate students, researchers and professional engineers.