Feature Selection Methods Best Practices: Data mining Approach (Paperback)

Subramanian Appavu alias Balamurugan

  • 出版商: LAP LAMBERT
  • 出版日期: 2012-06-25
  • 售價: $2,210
  • 貴賓價: 9.5$2,100
  • 語言: 英文
  • 頁數: 64
  • 裝訂: Paperback
  • ISBN: 3659164518
  • ISBN-13: 9783659164514
  • 相關分類: Data-mining 資料探勘
  • 下單後立即進貨 (約1週~2週)


Feature selection is a term commonly used in data mining to describe the tools and techniques available for reducing inputs to a manageable size for processing and analysis. Feature selection implies not only cardinality reduction, which means imposing an arbitrary or predefined cutoff on the number of attributes that can be considered when building a model, but also the choice of attributes, meaning that either the analyst or the modeling tool actively selects or discards attributes based on their usefulness for analysis. “Feature selection methods best Practices” is the mast reference that practitioners and researchers have long been seeking. It is also the obvious choice for academic and research scholars.