This book provides readers with the background and fundamental ideas behind Feature Selection (FS), with an emphasis on techniques based on rough and fuzzy sets. For readers who are less familiar with the subject, the book begins with an introduction to fuzzy set theory and fuzzy-rough set theory. Next it provides a critical review of FS methods with an emphasis on their current limitations, program files used to implement major algorithms, and associated areas of FS, including rule induction and clustering methods using hybridization of fuzzy and rough set theories.