LFD Book Forum Regression and VC dimension

#1
04-27-2012, 11:07 PM
 Mikhail Junior Member Join Date: Apr 2012 Posts: 3
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.
#2
04-28-2012, 12:00 AM
 yaser Caltech Join Date: Aug 2009 Location: Pasadena, California, USA Posts: 1,477
Re: Regression and VC dimension

Quote:
 Originally Posted by Mikhail 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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