Principles of Nonparametric Learning
Description
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.
Keywords
Technology & EngineeringElectronicsComputersMathematical & Statistical SoftwareComputer Vision & Pattern RecognitionMathematicsProbability & StatisticsImaging SystemsElectricalDiscrete MathematicsOptical Data Processing
2002Book
Author(s)Laszlo Györfi
PublisherSpringer Science & Business Media
ISBN9783211836880
LanguageEnglish
