[R] e1071/svm?

[Alexander Skomorokhov]

Thank you fot your reply. Sorry, but I still haven't got the problem.
Here is a trivial example (cpy from R session):
----------------------------------------------------------------------------
------------------
> x
     [,1] [,2]
[1,]    0    0
[2,]    0    1
[3,]    1    0
[4,]    1    1
[5,]    2    2
[6,]    2    3
[7,]    3    2
[8,]    3    3
> y
[1] 1 1 1 1 2 2 2 2
Levels:  1 2
> is.factor(y)
[1] TRUE
> library(e1071)
> m<-svm(x,y,kernel='linear')
*
optimization finished, #iter = 3
nu = 0.250000
obj = -1.000000, rho = -3.000000
nSV = 2, nBSV = 2
Total nSV = 2

> summary(m)
Call:
 svm.default(x = x, y = y, kernel = "linear")
Parameters:
   SVM-Type:  C-classification
 SVM-Kernel:  linear
       cost:  1
     degree:  3
      gamma:  0.5
     coef.0:  0
         nu:  0.5
    epsilon:  0.5
       cost:  1
Number of Support Vectors:  2  ( 1 1 )
Number of Classes:  2
Levels:
 1 2
Rho:
 -3
Support Vectors:
     [,1] [,2]
[1,]    1    1
[2,]    2    2
Coefficiants:
     [,1]
[1,]    1
[2,]   -1
----------------------------------------------------------------------------
----------
I see Coefficiants, but can't guess how to use them (only them?) for
prediction???
I may guess that the question sounds like a stupid one, but it is that:-(

Thanks,
Alexander.





> -----Original Message-----
> From: meyer at ci.tuwien.ac.at [mailto:meyer at ci.tuwien.ac.at]On
> Behalf Of David Meyer
> Sent: Thursday, December 20, 2001 3:03 PM
> To: askom at obninsk.com
> Cc: r-help
> Subject: Re: [R] e1071/svm?
>
>
> Alexander Skomorokhov wrote:
> >
> > Hello,
> >
> > I use function "svm" (interface to libsvm) from package e1071.
> It works just
> > fine.
> > And I may predict with function "predict" and svm model trained
> by function
> > "svm".
> > What I need is moving results of svm training to another
> application (non-R)
> > and
> > perform prediction there. But function "svm" returns list of
> support vectors
> > only
> > and doesn't return coefficients of separating hyperplane (w).
>
> It does (element ``coefs'' of the returned object).
>
> g.
> -d
>
> >
> > So, the question is how to use results of svm training to write
> (in other
> > language)
> > prediction function for linear and nonlinear cases?
> >
> > Thanks,
> > Alexander.
> >
> >
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	Mag. David Meyer		Wiedner Hauptstrasse 8-10
Vienna University of Technology		A-1040 Vienna/AUSTRIA
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