I've built an SVM model and the accuracy is quite good, the only problem is to plot the classification graph (For test data). I tried the way we usually do with the Iris data-set but getting I keep getting an error.
Code that I tried:
m2 <- svm(all~., data = sdfd) 
plot(m2, sdfd, Std.Dev ~ Var)#,
Here sdfd is the dataset in which the first column, all, is the factor of five values(in total 115). After execution of model I got:  
Parameters:
   SVM-Type:  C-classification 
 SVM-Kernel:  radial 
       cost:  1 
      gamma:  0.001052632 
Number of Support Vectors:  115
then when I tried to plot the classification chart I got this error:
Code that I tried:
plot(m2, sdfd, Std.Dev ~ Var,
     slice = list(Skew = 3, Kur = 3))# 
here, Skew and Kurt are two columns in my data-set. Though I wanted to plot the classification graph for eight columns together(I have 8 columns in my data), I realize that having eight columns and five factors are not possible to plot(Dimension wise). So I tried to plot pairwise. The error that I am getting is:
Error in Summary.factor(c(103L, 102L, 110L, 84L, 92L, 93L, 94L, 88L, 69L,: ‘min’ not meaningful for factors
What I wanted to plot is similar to this:
data(iris) 
m2 <- svm(Species~., data = iris) 
plot(m2, iris, Petal.Width ~ Petal.Length,
     slice = list(Sepal.Width = 3, Sepal.Length = 6))
It is really very helpful if someone can tell me how can i plot with five factors and 8 columns classification graph, but if someone can suggest me the solution of above error it would be equally helpful too.
 
    