{ "item_title" : "A Probabilistic Theory of Pattern Recognition", "item_author" : [" Luc Devroye", "Laszlo Györfi", "Gabor Lugosi "], "item_description" : "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, tree 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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/0/38/794/618/0387946187_b.jpg", "price_data" : { "retail_price" : "159.00", "online_price" : "159.00", "our_price" : "159.00", "club_price" : "159.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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