[R] Cross-validation accuracy in SVM

[Ton van Daelen]

Hi all -

I am trying to tune an SVM model by optimizing the cross-validation
accuracy. Maximizing this value doesn't necessarily seem to minimize the
number of misclassifications. Can anyone tell me how the
cross-validation accuracy is defined? In the output below, for example,
cross-validation accuracy is 92.2%, while the number of correctly
classified samples is (1476+170)/(1476+170+4) = 99.7% !?

Thanks for any help.

Regards - Ton

---
Parameters:
   SVM-Type:  C-classification 
 SVM-Kernel:  radial 
       cost:  8 
      gamma:  0.007 

Number of Support Vectors:  1015

 ( 148 867 )

Number of Classes:  2 

Levels: 
 false true

5-fold cross-validation on training data:

Total Accuracy: 92.24242 
Single Accuracies:
 90 93.33333 94.84848 92.72727 90.30303 

Contingency Table
           predclasses
origclasses false true
      false 1476     0
      true     4   170