A Probabilistic Theory of Pattern Recognition

Front Cover
Springer Science & Business Media, Apr 4, 1996 - Computers - 636 pages
3 Reviews
Pattern recognition presents one of the most significant challenges for scientists and engineers, and many different approaches have been proposed. The aim of this book is to provide a self-contained account of probabilistic analysis of these approaches. The book includes a discussion of distance measures, nonparametric methods based on kernels or nearest neighbors, Vapnik-Chervonenkis theory, epsilon entropy, parametric classification, error estimation, free classifiers, and neural networks. Wherever possible, distribution-free properties and inequalities are derived. A substantial portion of the results or the analysis is new. Over 430 problems and exercises complement the material.
  

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Contents

II
1
III
9
IV
11
V
12
VI
14
VII
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VIII
17
IX
18
CXIII
315
CXIV
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CXV
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CXVI
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CXVII
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CXVIII
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CXIX
332
CXX
333

X
21
XI
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XII
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XIII
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XIV
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XV
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XVII
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XVIII
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XIX
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XX
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XXI
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XXII
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XXIII
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XXIV
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XXV
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XXVI
56
XXVII
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XXVIII
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XXIX
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XXX
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XXXI
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XXXII
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XXXIII
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XXXIV
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XXXV
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XXXVII
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XXXVIII
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XXXIX
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XL
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XLI
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XLIII
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XLIV
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XLV
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XLVII
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XLVIII
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LXI
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XCIII
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XCIV
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XCV
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XCVI
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XCVII
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XCVIII
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XCIX
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C
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CI
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CII
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CIII
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CIV
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CV
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CVI
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CVIII
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CIX
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CX
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CXII
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CXXI
334
CXXII
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CXXIV
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CXXVII
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CXXVIII
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CXXIX
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CXXX
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CXXXV
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CXXXVI
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CXXXVII
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CXXXVIII
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CXXXIX
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CXLI
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CXLIII
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CL
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CLXX
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CLXXX
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CLXXXIV
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CLXXXV
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CLXXXVI
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CLXXXVII
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CLXXXVIII
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CLXXXIX
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CXC
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CXCI
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CXCII
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CXCIII
531
CXCIV
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CXCV
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CXCVI
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CXCVII
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CXCVIII
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CXCIX
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CCI
559
CCII
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CCIII
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CCIV
569
CCV
572
CCVI
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CCVIII
576
CCIX
579
CCX
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CCXI
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CCXII
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CCXIII
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CCXIV
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CCXV
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CCXVII
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CCXIX
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CCXX
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CCXXI
619
CCXXII
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About the author (1996)

G bor Lugosi has been working on various problems in pattern classification, nonparametric statistics, statistical learning theory, game theory, probability, and information theory. He is co-author of the monographs, A Probabilistic Theory of Pattern Recognition and Combinatorial Methods of Density Estimation. He has been an associate editor of various journals including The IEEE Transactions of Information Theory, Test, ESAIM: Probability and Statistics and Statistics and Decisions.