Solved – Why is it desirable to have linear separability in SVM

classificationmachine learningseparationsvm

enter image description here

Ref to above image, clearly a circle can separate the two classes(left image). Why then take so much pain to map it to a function to make it linearly separable (right image) ?

Can anyone please explain ? I really couldn't find anything on the web or youtube lectures on the why

Best Answer

Well, that is the whole idea behind support vector machines! svm are searching for a hyperplane that separates the classes (why the name), and that can of course be done most effectively it the points are linearly separable (that's not a deep point, it is a summary of the full idea). In the example you show, point lie on concentric annular rings, which cannot be separated by any plane, but by introducing a new variable RADIUS---distance from center---you get complete linear separation.

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