Comment by loehnsberg
3 years ago
A hyperplane is a multi-dimensional linear function that splits space into two distinct regions. In the context of a classifier, it splits feature space into disjunct sub-spaces (one for each class). SVMs effectively place a hyperplane with maximum margin, thereby separating classes in an optimal way.
Worth keeping in mind that though it may be optimal according to some mathematical criterion, that is no guarantee that it's the best for the purposes you have in mind.