Machine learning : modeling data locally and globally

著者

    • Huang, Kai-Zhu

書誌事項

Machine learning : modeling data locally and globally

Kai-Zhu Huang ... [et. al.]

(Advanced topics in science and technology in China)

Springer , Zhejibng University Press, c2008

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内容説明・目次

内容説明

"Machine Learning - Modeling Data Locally and Globally" presents a novel and unified theory that tries to seamlessly integrate different algorithms. Specifically, the book distinguishes the inner nature of machine learning algorithms as either 'local learning' or 'global learning'. This theory not only connects previous machine learning methods, or serves as roadmap in various models, but - more importantly - it also motivates a theory that can learn from data both locally and globally. This would help the researchers gain a deeper insight and comprehensive understanding of the techniques in this field. The book reviews current topics,new theories and applications. Kaizhu Huang was a researcher at the Fujitsu Research and Development Center and is currently a research fellow in the Chinese University of Hong Kong. Haiqin Yang leads the image processing group at HiSilicon Technologies. Irwin King and Michael R. Lyu are professors at the Computer Science and Engineering department of the Chinese University of Hong Kong.

目次

Introduction.- Global Learning vs. Local Learning: A Background Review.- A General Global Learning Model.- Learning Locally and Globally.- Application I: Imbalanced Learning.- Application II: Regression.- Summary.

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詳細情報

  • NII書誌ID(NCID)
    BA87188042
  • ISBN
    • 9783540794516
  • 出版国コード
    gw
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    Berlin,Hangzhou
  • ページ数/冊数
    x, 169 p.
  • 大きさ
    25 cm
  • 分類
  • 件名
  • 親書誌ID
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