Principles of Nonparametric Learning - CISM International Centre for Mechanical Sciences 434 (Paperback)Laszlo Gyorfi (editor)
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This volume provides a systematic in-depth analysis of nonparametric learning. It covers the theoretical limits and the asymptotical optimal algorithms and estimates, such as pattern recognition, nonparametric regression estimation, universal prediction, vector quantization, distribution and density estimation, and genetic programming.
Publisher: Springer Verlag GmbH
Number of pages: 335
Weight: 602 g
Dimensions: 244 x 170 x 19 mm
Edition: Softcover reprint of the original 1st ed. 200
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