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 Mikhail 04-28-2012 12:07 AM

Regression and VC dimension

In this course VC dimension was introduced by means of maximal number of points can be shuttered by the hypothesis set (if I'm not mistaken). It is clear for the classification, that we deal with dichotomies of {+1, -1} points. Well, but how does it relate to the regression model, when we learn f: R^n -> R? Clarify, please.

Thanks.

 yaser 04-28-2012 01:00 AM

Re: Regression and VC dimension

Quote:
 Originally Posted by Mikhail (Post 1638) In this course VC dimension was introduced by means of maximal number of points can be shuttered by the hypothesis set (if I'm not mistaken). It is clear for the classification, that we deal with dichotomies of {+1, -1} points. Well, but how does it relate to the regression model, when we learn f: R^n -> R? Clarify, please. Thanks.
The definition is technically modified, borrowing some concepts from measure theory. Look up the book by Vapnik.

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