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A rigorous theoretical treatment of pattern recognition grounded in probability theory and statistics, focusing on classification, nonparametric methods, consistency, rates of convergence, and learning theory, with emphasis on mathematical foundations rather than algorithmic heuristics.

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245: $a: A Probabilistic Theory of Pattern Recognition
245: $b:
082: $a:
100: $a: Luc Devroye & László Györfi & Gábor Lugosi
650: $a: Pattern recognition
250: $a:
440: $v:
250: $b: Springer (Springer-Verlag / Springer New York)
250: $c: 1996
020: $a: 978-0-387-94618-7
300: $a: 550