int *weight_label;
double* weight;
double p;
+ double *init_sol;
};
solver_type can be one of L2R_LR, L2R_L2LOSS_SVC_DUAL, L2R_L2LOSS_SVC, L2R_L1LOSS_SVC_DUAL, MCSVM_CS, L1R_L2LOSS_SVC, L1R_LR, L2R_LR_DUAL, L2R_L2LOSS_SVR, L2R_L2LOSS_SVR_DUAL, L2R_L1LOSS_SVR_DUAL.
If you do not want to change penalty for any of the classes,
just set nr_weight to 0.
+ init_sol includes the initial weight vectors (supported for only some
+ solvers). See the explanation of the vector w in the model
+ structure.
+
*NOTE* To avoid wrong parameters, check_parameter() should be
called before train().
}
if(param_tmp->C > max_C)
- info("warning: maximum C reached.\n");
+ info("WARNING: maximum C reached.\n");
free(target);
for(i=0; i<nr_fold; i++)
free(prev_w[i]);
return "unknown solver type";
if(param->init_sol != NULL
- && param->solver_type != L2R_LR && param->solver_type != L2R_L2LOSS_SVC)
- return "Initial-solution specification supported only for solver L2R_LR and L2R_L2LOSS_SVC";
+ && param->solver_type != L2R_LR
+ && param->solver_type != L2R_L2LOSS_SVC
+ && param->solver_type != L2R_L2LOSS_SVR)
+ return "Initial-solution specification supported only for solvers L2R_LR, L2R_L2LOSS_SVC, and L2R_L2LOSS_SVR";
return NULL;
}