Principles of Nonparametric Learning

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Principles of Nonparametric Learning by László Györfi
English | Sep. 10, 2002 | ISBN: 3211836888 | 344 Pages | PDF | 24 MB

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.

Title: Principles of Nonparametric Learning
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