[R] e1071 SVM: Cross-validation error confusion matrix
Frank Harrell
f.harrell at vanderbilt.edu
Sun Dec 2 20:36:56 CET 2012
What do you mean by accuracy? Proportion classified correctly is not a good
index of accuracy if that's the problem.
Frank
rahul143 wrote
> 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,
-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
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