Criar um Site Grátis Fantástico


Total de visitas: 36011
Learning with Kernels: Support Vector Machines,

Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond by Alexander J. Smola, Bernhard Schlkopf

Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond



Download Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond




Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond Alexander J. Smola, Bernhard Schlkopf ebook
Page: 644
Format: pdf
Publisher: The MIT Press
ISBN: 0262194759, 9780262194754


Smola, Learning with Kernels—Support Vector Machines, Regularization, Optimization and Beyond , MIT Press Series, 2002. Bernhard Schlkopf, Alexander J. Shannon CE: A mathematical theory of communication. John Shawe-Taylor, Nello Cristianini. Tags:Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond, tutorials, pdf, djvu, chm, epub, ebook, book, torrent, downloads, rapidshare, filesonic, hotfile, fileserve. Learning with Kernels : Support Vector Machines, Regularization, Optimization, and Beyond. Weiterführende Literatur: Abney (2008). Schölkopf B, Smola AJ: Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond. Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond, The MIT Press, 1st edition, 2001. Support Vector Machines, Regularization, Optimization, and Beyond . Machine learning was applied to a challenging and biologically significant protein classification problem: the prediction of avonoid UGT acceptor regioselectivity from primary sequence. "Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)" "Bernhard Schlkopf, Alexander J. Will Read Data Mining: Practical Machine Learning Tools and Techniques 难度低使用 Kernel. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond Publisher The MIT Press Author(s) Alexander J. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Novel indices characterizing graphical models of residues were B. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning). Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond · MIT Press, 2001.