You are given a dataset with the following statistics: # examples $=500,$ #attributes$=20,$ #classes$=2.$ You are pretty sure that the data is linearly separable. You perform $5-$fold cross validation on the dataset using linear support vector machines and decision trees $($ID$3)$ and obtain the following results.

Table $1$

WherError

Fold$1$ Error

Fold$2$ Error

Fold$3$ Error

Fold$4$ Error

Fold$5$ Average

Error

Linear SVM $1/1000/1001/10030/1001/10033/500$

ID$37/1004/1005/1004/1005/10025/500$e Error $=$ #mis$-$classified examples $/$ #test$-$examples

Your friend looks at Table $1$ and concludes that ID$3$ is the best performing scheme for datasets of this type. Can you support his$/$her conclusion