An elementary introduction to statistical learning theory /

• Main Author: Kulkarni, Sanjeev
• Corporate Author: Wiley InterScience (Online service)
• Other Authors: Harman, Gilbert
• Format: eBook
• Language: English
• Published: Hoboken, N.J. : Wiley, [2011]
• Series: Wiley series in probability and statistics.
• Subjects: Machine learning > Statistical methods.; Pattern recognition systems.; Artificial Intelligence.; Pattern Recognition, Automated.; Statistics as Topic.; Aprenentatge automàtic > Mètodes estadístics.; Reconeixement de formes (Informàtica); COMPUTERS > Enterprise Applications > Business Intelligence Tools.; COMPUTERS > Intelligence (AI) & Semantics.; Maschinelles Lernen.; Statistik.; Llibres electrònics.; Electronic books.

"A joint endeavor from leading researchers in the fields of philosophy and electrical engineering An Introduction to Statistical Learning Theory provides a broad and accessible introduction to rapidly evolving field of statistical pattern recognition and statistical learning theory. Exploring t...

Table of Contents:

• Introduction: Classification, Learning, Features, and Applications
• Probability
• Probability Densities
• The Pattern Recognition Problem
• The Optimal Bayes Decision Rule
• Learning from Examples
• The Nearest Neighbor Rule
• Kernel Rules
• Neural Networks: Perceptrons
• Multilayer Networks
• PAC Learning
• VC Dimension
• Infinite VC Dimension
• The Function Estimation Problem
• Learning Function Estimation
• Simplicity
• Support Vector Machines
• Boosting.