The latest support vector machine toolbox, it will be very convenient to have it. 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] VN Vapnik, \"The Nature of Statistical Learning Theory\", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] JC Platt, \"Fast training of support vector machines using sequential minimal optimization\", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and AJ Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, \"Estimating the Generalization Performance of a SVM Efficiently\", LS-8 Report 25, University of Dortmund, Fachbereich Informatik, 1999.
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