SPIDER The Spider Objects

SVR object

   A=SVR(H) returns a svr object initialized with hyperparameters H. 
    Hyperparameters, and their defaults
     C=Inf;               -- the soft margin C parameter
     optimizer='andre';  -- other choices={quadprog,andre,libsvm,svmtorch,sparse}
     alpha_cutoff=-1;     -- keep alphas with abs(a_i)>alpha_cutoff
     nu = 0;              -- nu parameter of a nu svr (different 
                             from zero implies the nu-SVR is used
                             otherwise, the epsilon-SVR is used)
     child=kernel;        -- the kernel is stored as a member called "child"
     epsilon=0.1;         -- the value of epsilon in the epsilon 
                             insensitive loss function during learning
     use_signed_output=0; -- set to 1 implies that the svr is used
                             in classification (+1/-1 outputs), set to 0 
                             implies that the svr is used in regression
     alpha                -- the weights
     b0                   -- the threshold
     Xsv                  -- the Support Vectors
     train, test, get_w 

Reference : A tutorial on Support Vector Regression
Author : Alex J. Smola , Bernhard Schölkopf
Link : http://citeseer.ist.psu.edu/smola98tutorial.html