/*-----------------------------------------------------------------------
 SMO algorithm for separable single-class SVM problem.

 int single_smo(TKerFun ker,
             long num_data,
             long tmax,
             double tolabs,
             double tolrel,
             double *Alpha,
             double *UB,
             double *LB,
             long *t,
             double *History)

 tmax, tolabs, tolrel ... Define stopping conditions: 

    UB <= tolabs              ->  exit_flag = 1   Abs. tolerance.
    (UB-LB)/(LB+1) <= tolrel  ->  exit_flag = 2   Relative tolerance.
    t >= tmax                 ->  exit_flag = 0   Number of iterations.
 
 Alpha ... Lagrangians defining found decision rule. 
 UB ... Achieved upper bound on the optimal solution.
 LB ... Achieved lower bound on the optimal solution.
 t  ... Number of iterations.
 History ... Value of LB and UB wrt. number of iterations.

 Modifications:
 23-Jan-2004, VF
-------------------------------------------------------------------- */

extern int single_smo(
            double (*kernel_fce)(long, long),
            long num_data, 
            long tmax,
            double tolabs,
            double tolrel,
            double **out_Alpha,
            double *out_UB,
            double *out_LB,
            long  *out_t,
            double **out_History);