-s 5 and 6
|f'(w)|_inf <= eps*min(pos,neg)/l*|f'(w0)|_inf,
where f is the primal function (default 0.01)
--B bias : if bias >= 0, instance x becomes [x; bias]; if < 0, no bias term added (default 1)
+-B bias : if bias >= 0, instance x becomes [x; bias]; if < 0, no bias term added (default -1)
-wi weight: weights adjust the parameter C of different classes (see README for details)
-v n: n-fold cross validation mode
-q : quiet mode (no outputs)
" -s 5 and 6\n"
" |f'(w)|_inf <= eps*min(pos,neg)/l*|f'(w0)|_inf,\n"
" where f is the primal function (default 0.01)\n"
- "-B bias : if bias >= 0, instance x becomes [x; bias]; if < 0, no bias term added (default 1)\n"
+ "-B bias : if bias >= 0, instance x becomes [x; bias]; if < 0, no bias term added (default -1)\n"
"-wi weight: weights adjust the parameter C of different classes (see README for details)\n"
"-v n: n-fold cross validation mode\n"
"-q : quiet mode (no outputs)\n"
param.weight = NULL;
cross_validation_flag = 0;
col_format_flag = 0;
- bias = 1;
+ bias = -1;
// train loaded only once under matlab
if(liblinear_default_print_string == NULL)
" -s 5 and 6\n"
" |f'(w)|_inf <= eps*min(pos,neg)/l*|f'(w0)|_inf,\n"
" where f is the primal function (default 0.01)\n"
- "-B bias : if bias >= 0, instance x becomes [x; bias]; if < 0, no bias term added (default 1)\n"
+ "-B bias : if bias >= 0, instance x becomes [x; bias]; if < 0, no bias term added (default -1)\n"
"-wi weight: weights adjust the parameter C of different classes (see README for details)\n"
"-v n: n-fold cross validation mode\n"
"-q : quiet mode (no outputs)\n"
param.weight_label = NULL;
param.weight = NULL;
flag_cross_validation = 0;
- bias = 1;
+ bias = -1;
// parse options
for(i=1;i<argc;i++)