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    Probabilistic Theory of Pattern Recognition

Probabilistic Theory of Pattern Recognition

Luc Devroye, Laszlo Gyoerfi, Gabor Lugosi
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      A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.
      Format: CONTRIBUTORS: Luc Devroye, Laszlo Gyoerfi, Gabor Lugosi EAN: 9780387946184 COUNTRY: United States PAGES: WEIGHT: 2420 g HEIGHT: 235 cm
      PUBLISHED BY: Springer-Verlag New York Inc. DATE PUBLISHED: 1997-02-20 CITY: GENRE: COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, MATHEMATICS / Probability & Statistics / General WIDTH: 155 cm SPINE:

      Book Themes:

      Probability and statistics, Stochastics, Pattern recognition

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      A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.
      Format: CONTRIBUTORS: Luc Devroye, Laszlo Gyoerfi, Gabor Lugosi EAN: 9780387946184 COUNTRY: United States PAGES: WEIGHT: 2420 g HEIGHT: 235 cm
      PUBLISHED BY: Springer-Verlag New York Inc. DATE PUBLISHED: 1997-02-20 CITY: GENRE: COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, MATHEMATICS / Probability & Statistics / General WIDTH: 155 cm SPINE:

      Book Themes:

      Probability and statistics, Stochastics, Pattern recognition

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