title: how use cross validation to determine cost in multi-classification svm
body: <p>HI I used the following for multi-classification in R. how I can choose the best cost with using cross-validation? </p>
  
  <pre><code>  n &lt;- nrow(hd) 
    ntrain &lt;- round(n*0.75)
    set.seed(314)
     tindex &lt;- sample(n, ntrain)
     train_iris &lt;- hd[tindex,]
     test_iris &lt;- hd[-tindex,] 
     svm1 &lt;- svm(res~., data=train_iris, 
          method="C-classification", kernal="radial", 
          gamma=0.1, cost=10)
  </code></pre>