如何调整SVM Rank的参数？

我正在使用SVM Rank，它具有多个参数，更改了我得到各种结果的人。是否有某种机制可以根据验证集上的最佳结果进行调整并获得最佳参数？

以下是不同的参数：

Learning Options:
     -c float    -> C: trade-off between training error
                    and margin (default 0.01)
     -p [1,2]    -> L-norm to use for slack variables. Use 1 for L1-norm,
                    use 2 for squared slacks. (default 1)
     -o [1,2]    -> Rescaling method to use for loss.
                    1: slack rescaling
                    2: margin rescaling
                    (default 2)
     -l [0..]    -> Loss function to use.
                    0: zero/one loss
                    ?: see below in application specific options
                    (default 1)
Optimization Options (see [2][5]):
     -w [0,..,9] -> choice of structural learning algorithm (default 3):
                    0: n-slack algorithm described in [2]
                    1: n-slack algorithm with shrinking heuristic
                    2: 1-slack algorithm (primal) described in [5]
                    3: 1-slack algorithm (dual) described in [5]
                    4: 1-slack algorithm (dual) with constraint cache [5]
                    9: custom algorithm in svm_struct_learn_custom.c
     -e float    -> epsilon: allow that tolerance for termination
                    criterion (default 0.001000)
     -k [1..]    -> number of new constraints to accumulate before
                    recomputing the QP solution (default 100)
                    (-w 0 and 1 only)
     -f [5..]    -> number of constraints to cache for each example
                    (default 5) (used with -w 4)
     -b [1..100] -> percentage of training set for which to refresh cache
                    when no epsilon violated constraint can be constructed
                    from current cache (default 100%) (used with -w 4)
SVM-light Options for Solving QP Subproblems (see [3]):
     -n [2..q]   -> number of new variables entering the working set
                    in each svm-light iteration (default n = q).
                    Set n < q to prevent zig-zagging.
     -m [5..]    -> size of svm-light cache for kernel evaluations in MB
                    (default 40) (used only for -w 1 with kernels)
     -h [5..]    -> number of svm-light iterations a variable needs to be
                    optimal before considered for shrinking (default 100)
     -# int      -> terminate svm-light QP subproblem optimization, if no
                    progress after this number of iterations.
                    (default 100000)
Kernel Options:
     -t int      -> type of kernel function:
                    0: linear (default)
                    1: polynomial (s a*b+c)^d
                    2: radial basis function exp(-gamma ||a-b||^2)
                    3: sigmoid tanh(s a*b + c)
                    4: user defined kernel from kernel.h
     -d int      -> parameter d in polynomial kernel
     -g float    -> parameter gamma in rbf kernel
     -s float    -> parameter s in sigmoid/poly kernel
     -r float    -> parameter c in sigmoid/poly kernel
     -u string   -> parameter of user defined kernel