e1071 SVM: Cross-validation error confusion matrix

Hi, 

I ran two svm models in R e1071 package: the first without cross-validation
and the second with 10-fold cross-validation. 

I used the following syntax: 

#Model 1: Without cross-validation:

svm.model <- svm(Response ~ ., data=data.df, type="C-classification",
kernel="linear", cost=1) 
predict <- fitted(svm.model) 
cm <- table(predict, data.df$Response) 
cm 

#Model2: With 10-fold cross-validation:

svm.model2 <- svm(Response ~ ., data=data.df, type="C-classification",
kernel="linear", cost=1, cross=10) 
predict2 <- fitted(svm.model2) 
cm2 <- table(predict2, data.df$Response) 
cm2 

However, when I compare cm and cm2, I notice that the confusion matrices are
identical although the accuracy of each model is diffent. What am I doing
wrong? 
  
Thanks for you help, 




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