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Foundations of Feature Selection

  • Verónica Bolón-Canedo
  • Noelia Sánchez-Maroño
  • Amparo Alonso-Betanzos
Part of the Artificial Intelligence: Foundations, Theory, and Algorithms book series (AIFTA)

Abstract

Abstract In order to confront the problem of the high dimensionality of data, feature selection algorithms have become indispensable components of the learning process. Therefore, a correct selection of the features can lead to an improvement of the inductive learner in terms of learning speed, generalization capacity or simplicity of the induced model. A global overview of the feature selection process is given in Section 2.1. Then, Section 2.2 describes the different types of feature selection methods, as well as providing a description of the most popular algorithms for further analysis and explanation in subsequent chapters of the book. Finally, Section 2.3 summarizes this chapter.

Keywords

Feature Selection Feature Subset Feature Selection Method Feature Selection Algorithm Feature Selection Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Verónica Bolón-Canedo
    • 1
  • Noelia Sánchez-Maroño
    • 1
  • Amparo Alonso-Betanzos
    • 1
  1. 1.Facultad de InformáticaUniversidad de A CoruñaA CoruñaSpain

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