Principles of Nonparametric Learning (CISM International Centre for Mechanical Sciences, 434, Band 434) - Softcover

Inhaltsangabe

The book provides 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. The book is mainly addressed to postgraduates in engineering, mathematics, computer science, and researchers in universities and research institutions.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.