| Parameters |
options: -s svm_type : set type of SVM (default 0) 0 -- C-SVC 1 -- nu-SVC 2 -- one-class SVM 3 --
epsilon-SVR 4 -- nu-SVR -t kernel_type : set type of kernel function (default 2) 0 -- linear:
u'*v 1 -- polynomial: (gamma*u'*v + coef0)^degree 2 -- radial basis function: exp(-gamma*|u-v|^2)
3 -- sigmoid: tanh(gamma*u'*v + coef0) 4 -- precomputed kernel (kernel values in
training_set_file) -d degree : set degree in kernel function (default 3) -g gamma : set gamma in
kernel function (default 1/num_features) -r coef0 : set coef0 in kernel function (default 0) -c
cost : set the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1) -n nu : set the
parameter nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5) -p epsilon : set the epsilon in
loss function of epsilon-SVR (default 0.1) -m cachesize : set cache memory size in MB (default
100) -e epsilon : set tolerance of termination criterion (default 0.001) -h shrinking : whether
to use the shrinking heuristics, 0 or 1 (default 1) -b probability_estimates : whether to train a
SVC or SVR model for probability estimates, 0 or 1 (default 0) -wi weight : set the parameter C
of class i to weight*C, for C-SVC (default 1) -v n : n-fold cross validation mode -q : quiet mode
(no outputs)
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