02604cam a22004574a 4500 8834492 BD-DhUL 20150219124343.0 m d cr n 101123s2011 njua sb 001 0 eng d 9780470641835 (cloth) 0470641835 (cloth) 9781118023433 1118023439 9781118023464 1118023463 9781118023471 1118023471 (WaSeSS)ssj0000476962 DLC DLC YDX CDX YDXCP OIP Z@L DEBBG DLC WaSeSS BD-DhUL pcc Q325.5 .K85 2011 006.31 22 KUE ST 300 rvk Kulkarni, Sanjeev. An elementary introduction to statistical learning theory An elementary introduction to statistical learning theory / Sanjeev Kulkarni, Gilbert Harman. Hoboken, N.J. : Wiley, c2011. xi, 209 p.: ill. ; 24 cm. US$ 89.06 Wiley series in probability and statistics Includes bibliographical references and indexes. 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 -- Bibliography. "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. Machine learning Statistical methods. Pattern recognition systems. Harman, Gilbert. Wiley series in probability and statistics. ddc BK 1316 1316 0 0 ddc 0 006_310000000000000_KUE 0 NFIC 2210 DUSL DUSL GEN 2012-09-22 purchased 006.31 KUE 475129 2014-08-08 2014-08-08 BK