"Usage: model = train(training_label_vector, training_instance_matrix, 'liblinear_options', 'col');\n"
"liblinear_options:\n"
"-s type : set type of solver (default 1)\n"
- " 0 -- L2 logistic regression\n"
+ " 0 -- L2-regularized logistic regression\n"
" 1 -- L2-loss support vector machines (dual)\n"
" 2 -- L2-loss support vector machines (primal)\n"
" 3 -- L1-loss support vector machines (dual)\n"
- " 4 -- multi-class support vector machines from Crammer and Singer\n"
+ " 4 -- multi-class support vector machines by Crammer and Singer\n"
"-c cost : set the parameter C (default 1)\n"
"-e epsilon : set tolerance of termination criterion\n"
" -s 0 and 2\n"