Does there some kind of a distance metric that they use or how do they  for cla what do they do for classification ?
Um. Right. So ,  the  the simple idea behind a support vector machine is  um ,  you have  you have this feature space , right ? and then it finds the optimal separating plane , um between these two different um classes ,
Mm - hmm. Mm - hmm. Mm - hmm.
and um  and so  um , what it  i at the end of the day , what it actually does is  it picks  those examples of the features that are closest to the separating boundary , and remembers those