Principles and theory for data mining and machine learning

著者

• Clarke, Bertrand
• Fokoué, Ernest
• Zhang, Hao Helen

書誌事項

Principles and theory for data mining and machine learning

Bertrand Clarke, Ernest Fokoué, Hao Helen Zhang

（Springer series in statistics）

Springer, c2009

注記

Includes bibliographical references (p. 743-771) and index

内容説明・目次

内容説明

Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging methods Range of topics drawn from Statistics, Computer Science, and Electrical Engineering

目次

Variability, Information, and Prediction.- Local Smoothers.- Spline Smoothing.- New Wave Nonparametrics.- Supervised Learning: Partition Methods.- Alternative Nonparametrics.- Computational Comparisons.- Unsupervised Learning: Clustering.- Learning in High Dimensions.- Variable Selection.- Multiple Testing.

「Nielsen BookData」 より

詳細情報

• NII書誌ID(NCID): BA9123046X
• ISBN:
  • 9780387981345
• LCCN: 2009930499
• 出版国コード: us
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: New York
• ページ数/冊数: xv, 781 p.
• 大きさ: 25 cm
• 分類:
  • DC22 : 006.31
• 件名:
  • LCSH : Data mining
  • LCSH : Machine learning -- Statistical methods
• 親書誌ID:
  • BA00018600