04824cam a2200949Ia 4500 ocn729724626 OCoLC 20171119084417.0 m o d cr cn||||||||| 110609s2011 njua ob 001 0 eng d 9781118023471 (electronic bk.) 1118023471 (electronic bk.) 9781118023433 (e-book) 1118023439 (e-book) 1283098687 9781283098687 9780470641835 9781118023464 (ePub) 0470641835 1118023463 AU@ 000047226102 AU@ 000047551214 AU@ 000051561706 DEBBG BV041910322 DEBBG BV042961309 DEBSZ 37272938X DEBSZ 372734472 DEBSZ 396995543 DEBSZ 421528567 DEBSZ 430992661 DEBSZ 449241793 DKDLA 820120-katalog:000572952 HEBIS 299829545 NZ1 13751530 NZ1 14256865 NZ1 15341319 AU@ 000058376262 DEBBG BV043393145 (OCoLC)729724626 (OCoLC)726329153 (OCoLC)732956377 (OCoLC)741451118 (OCoLC)754717771 (OCoLC)778448327 (OCoLC)816840042 10.1002/9781118023471 Wiley InterScience http://www3.interscience.wiley.com DG1 eng pn DG1 IDEBK YDXCP E7B CDX OCLCQ COD N$T OCLCQ DEBSZ OCLCQ OCLCA UKDOC OCLCQ RIV NLGGC OCLCQ OCLCF DEBBG OCLCQ COO OCLCQ MAIN Q325.5 .K85 2011 Q 325.5 COM 005030 bisacsh COM 004000 bisacsh 006.3/1 22 Kulkarni, Sanjeev. An elementary introduction to statistical learning theory / Sanjeev Kulkarni, Gilbert Harman. [electronic resource] Hoboken, N.J. : Wiley, ©2011. 1 online resource (1 volume) : illustrations. text txt rdacontent computer c rdamedia online resource cr rdacarrier Wiley series in probability and statistics Includes bibliographical references and index. 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. "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. Print version record. 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. bisacsh COMPUTERS Intelligence (AI) & Semantics. bisacsh Machine learning Statistical methods. fast (OCoLC)fst01004801 Pattern recognition systems. fast (OCoLC)fst01055266 Maschinelles Lernen. (DE-588c)4193754-5 swd Statistik. (DE-588c)4056995-0 swd Llibres electrònics. Electronic books. Harman, Gilbert. Wiley InterScience (Online service) Print version: Kulkarni, Sanjeev. Elementary introduction to statistical learning theory. Hoboken, N.J. : Wiley, ©2011 9781118023471 (OCoLC)726329153 Wiley series in probability and statistics. http://onlinelibrary.wiley.com/book/10.1002/9781118023471 Wiley Online Library ddc BK 205074 205074