Linear SVM with Gamma Parameter

Question

I was running a Linear SVM with e1071 and tuning the Cost and Epsilon parameters. However, I noticed when I printed my model, a Gamma Parameter was also present. Why is that? I thought Gamma was only for Radial Kernels? I restarted my R to make sure I got the same result and only e1071 was loaded.

In addition, looking at the package contents of e1071 , for regression, we have:

gamma = parameter needed for all kernels except linear (default: 1/(data dimension)) (pg. 50) here

This implies that gamma should be omitted for linear kernels, but it is not. Have others experienced this as well?

Furthermore, I have tried it with other values of gamma and received the same results indicating to me the gamma parameter is ignored, but I am looking for validation from others to see if they have similar answers and an explanation as to why Gamma is present.

library(e1071)
set.seed(1)
model<-svm(Sepal.Length~Sepal.Width+Petal.Length,
            data=iris,
            kernel='linear',
            cost=0.5,
            epsilon=0.1,
            cross=10
)
model
Parameters:
   SVM-Type:  eps-regression 
 SVM-Kernel:  linear 
       cost:  0.5 
      gamma:  0.5
    epsilon:  0.1 
coef(model)
(Intercept)  Sepal.Width Petal.Length 
 -0.01487154   0.31124329   0.97591508 
modelG2<-svm(Sepal.Length~Sepal.Width+Petal.Length,
           data=iris,
           kernel='linear',
           cost=0.5,
           epsilon=0.1,
           gamma=2,
           cross=10
)
modelG2
Parameters:
   SVM-Type:  eps-regression 
 SVM-Kernel:  linear 
       cost:  0.5 
      gamma:  2 
    epsilon:  0.1 
coef(modelG2)
(Intercept)  Sepal.Width Petal.Length 
 -0.01487154   0.31124329   0.97591508 

modelG17<-svm(Sepal.Length~Sepal.Width+Petal.Length,
             data=iris,
             kernel='linear',
             cost=0.5,
             epsilon=0.1,
             gamma=17,
             cross=10
)
modelG17
coef(modelG17)
(Intercept)  Sepal.Width Petal.Length 
 -0.01487154   0.31124329   0.97591508