# Can 2 dimensional input be applied to SVM? [closed]

When considering Support Vector Machine, in an take in multiple inputs. Can each of these inputs be a vector?? What i am trying to say is, can the input be a 2 dimensional vector??

• It's not clear what you mean. Is the input to SVM a vector? yes, that's true for most ML algorithms. Multiple vectors? yes, training happens on > 1 data point. 2D? yes. Somehow, several 2D vectors at once? not clear what that means. Please clarify. – Sean Owen Jan 31 '15 at 11:32

## 1 Answer

If I understand your question correctly. Yes, SVM can take multiple inputs. My suggestion for handling a vector as a feature would be to expand it out. For example,

x0 = (1,2)       x0 = 1
x1 = .4  ----->  x1 = 2
x2 = 0           x2 = .4
x3 = 0


If this does not capture all of the characteristics of the vector that are important, then you may want to add other features (like magnitude of the vector) as well.

• ok, so if one of the input is 2d then it is expanded, yes, this is exactly what i wanted to know... thanks a lot – girl101 Jan 31 '15 at 9:56