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.
• Physical Description: 1 online resource (1 volume) : illustrations.
• Bibliography: Includes bibliographical references and index.
• ISBN: 9781118023471; 1118023471; 9781118023433; 1118023439; 1283098687; 9781283098687
• DOI: 10.1002/9781118023471

"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 topics that are not often covered in introductory level books on statistical learning theory, including PAC learning, VC dimension, and simplicity, the authors present upper-undergraduate and graduate levels with the basic theory behind contemporary machine learning and uniquely suggest it serves as an excellent framework for philosophical thinking about inductive inference"--Back cover.