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From: Daniel on 3 Jun 2010 10:13
"Bruno Luong" <b.luong(a)fogale.findmycountry> wrote in message <hnndb3$a6q$1(a)fred.mathworks.com>...
> "Ibraheem " <ibr_ex(a)hotmail.com> wrote in message <hnmql4$osg$1(a)fred.mathworks.com>...
> > Hi Bruno,
> > >http://www.mathworks.com/matlabcentral/newsreader/view_thread/260308#679215
> > > replace "w'*x" by kernel operator applied on w and x.
> > Thank you again for your concern and quick reply.
> > I have read your post but I can not understand the notation.
> > Do you mean :
> > W = sum( lambda*Y*X);
> > b = -1/2 ( mean (SV(SV(2)<0)) W'*X + mean(SV(SV(2)>0)) W'*X);
>
> > I don't understand two things:
> > 1. Does the mean for all matrix or for the second column only.
>
> For a data #i, Yi is class (or group +/--1) of the data Xi (a vector observation in R^n, its is one row of the training data your pass to svmclassify), and lambda_i is the dual variable (scalar) returned. Multiply these three term and add them together (sum on i), you get a vector W. Next compute b which is a scalar.
>
> > 2. What is the dual variable ? Is it alpha ?
> > Sorry for bothering and regards,
>
> Matlab classify returns in Alpha the product (Yi*lambdai_i) after training.
>
> Bruno

where i can find lambda? is alpha=Yi*lambda?
and i'm doing some project using svm and my case is non-linear separable case, in non-linear there is variable C, how can i adjust variable C in svmtrain?


regards
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