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017 _a174142074.
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020 _a9780470140529
020 _a9780470140512
_q(electronic bk.)
024 7 _a10.1002/9780470140529
_2doi
040 _aES-VaUE
_beng
_cES-VaUE
_dES-VaUE
050 4 _aTK5102.9
_b2007 EB
100 1 _aCherkassky, Vladimir S.
_9518932
_eautor
245 1 0 _aLearning from data :
_bConcepts, theory, and methods
_cby Vladimir Cherkassky and Filip Mulier
250 _a2nd ed 2007
264 _aHoboken, N.J.
_bIEEE Press
_c2007
300 _a1 recurso en línea
336 _2rdacontent
_aTexto (visual)
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
504 _aIncluye índice y referencias bibliográficas (páginas 519-531)
505 0 _aProblem statement, classical approaches, and adaptive learning -- Regularization framework -- Statistical learning theory -- Nonlinear optimization strategies -- Methods for data reduction and dimensionality reduction -- Methods for regression -- Classification -- Support vector machines -- Noninductive inference and alternative learning formulations
520 _aAn interdisciplinary framework for learning methodologies--covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied--showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science
988 _aEbook_one2one
650 7 _2embne
_920920
_aIngeniería del software
700 1 _aMulier, Filip
_9518933
_eautor
856 4 0 _uhttps://secure-web.cisco.com/1UZFoPBZ1K8dwi2fpWV9bseWN8cJXK0VBiio8VVhDv04UtYGBuwatS2nBdl8CIlRhubjqNIWLQw4AjSY2q6UoFIYvh8He-rOXgF0qZGyvJSb4rturaw9sFCeK3G_ZZmW6VcuyEZthRE_9siGsduEn-XJSmcvdhysQenBEKV0vI0QghV8kjRn-t9R5jOFnmX5GIY2JdViefrVrkpyxMMUPbGhwME1wUI8l-KRvGEbIM55bvoECTJYaxZeSqrvN-BiJxDl1fDreIvFSoxjbzrXjSI4vcTOluCelrC10kD43jAfxOyBx4KpWSXSz2P35egYBFSiCQEkidL2soImToAgl0Q/https%3A%2F%2Fsearch.ebscohost.com%2Flogin.aspx%3Fdirect%3Dtrue%26scope%3Dsite%26db%3Dnlebk%26db%3Dnlabk%26AN%3D207850
_zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942 _2lcc
_cLE
998 _b07/2024
_db
_eb
_zSI