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, data=dat, kernel="radial", cost=10, gamma=1)
> plot(svmfit, dat)
The e1071 library can also be used to perform support vector regression, if the response vector that is passed in to svm() is numerical rather than a factor
from the top result below
https://listcomp.com/machine-learning/2014/10/08/isl-support-vector-machines
2} \end{equation}\]
If a separating hyperplane exists, we can use it to construct a very natural classifier: a test observation is assigned a class depending on which side of the hyperplane it is located