[R] SVM linear kernel and SV

[David Meyer]

> Thank you for your answer,
> but my problem concerns the support vectors. Indeed the two classes
> are well separated and the hyperplane is linear but the support
> vectors aren't aligned in parallel to the hyperplane. And according to
> me,  the support vectors (for each class) should be aligned along the
> linear hyperplane and form the marge (by definition). But it's not the
> case. In fact,  I'd like to understand why they are not aligned. 

Remember the `cost'-penalty controlling for overlapping classes. It has
some effect even in the linearly separable case causing more SVs than
would actually be needed. Try adding e.g. `cost=1000' and you will
obtain a result with only 2 SVs (why not 3? Because 2 SVs here solve the
optimization problem. So in fact the hyperplane in this case is not
uniquely defined, although only in a small range.)

Best,

David