Lets generate random data

  x  y
1 1  3
2 2  4
3 3  5
4 4  4
5 5  8
6 6 10

Generate Linear Map

Fit a SVM model


Call:
svm(formula = y ~ x, data = train)


Parameters:
   SVM-Type:  eps-regression 
 SVM-Kernel:  radial 
       cost:  1 
      gamma:  1 
    epsilon:  0.1 


Number of Support Vectors:  9

Use PREDICTIONS ON THE DATA

Plot the predictios and the plot to see our model fit

MSE Comparison

[1] 2.696281
[1] 3.832974