R help - May 2010 - Question regarding GBM package

Dear R expert

I have  come across the GBM package for R and it seemed appropriate for my
research. I am trying to predict the number of FPGA resources required by a
Software Function if it were mapped onto hardware. As input I use software
metrics (a lot of them). I already use several regression techniques, and
the graphs I produce with GBM look promising.

Now my question... I see that the output of the GBM package gives (when
using cross-validation) also an array called cv.error. How might I obtain
the Cross-Validated Rooted Mean Square Error  from that data? Or is there
another approach to that?
Also I would like to have a plot of the cross-validated predictions versus
the original data, I could do this by manually performing Leave-One-Out and
getting the predictions for the plot, but as GBM incorporates
Cross-Validation I was wondering if there is an easier approach.

I hope someone can point me in the right direction. Many thanks for any help
anyone might be able to give.

kind regards,

Roel Meeuws
--------------------------------------------
Roel Meeuws
PhD. Student
Delft University of Technology
Faculty of Electrical Engineering Mathematics and Computer Science
Computer Engineering Laboratory
Mekelweg 4, 2628 CD Delft, The Netherlands
--------------------------------------------
Email:r.j.meeuws@tudelft.nl <Email%3Ar.j.meeuws@tudelft.nl>
Office: HB 16.290
Office phone: +31 (0)15 27 82 165
Mob. phone: +31 (0)6 10 82 44 01
--------------------------------------------

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The caret package can do a lot of that for you:

   http://www.jstatsoft.org/v28/i05/paper
   http://cran.r-project.org/web/packages/caret/index.html
   http://cran.r-project.org/web/packages/caret/vignettes/caretTrain.pdf

Max


On Fri, May 21, 2010 at 8:05 AM, Roel Meeuws <r.j.meeuws at tudelft.nl>
wrote:
> Dear R expert
>
> I have ?come across the GBM package for R and it seemed appropriate for my
> research. I am trying to predict the number of FPGA resources required by a
> Software Function if it were mapped onto hardware. As input I use software
> metrics (a lot of them). I already use several regression techniques, and
> the graphs I produce with GBM look promising.
>
> Now my question... I see that the output of the GBM package gives (when
> using cross-validation) also an array called cv.error. How might I obtain
> the Cross-Validated Rooted Mean Square Error ?from that data? Or is there
> another approach to that?
> Also I would like to have a plot of the cross-validated predictions versus
> the original data, I could do this by manually performing Leave-One-Out and
> getting the predictions for the plot, but as GBM incorporates
> Cross-Validation I was wondering if there is an easier approach.
>
> I hope someone can point me in the right direction. Many thanks for any
help
> anyone might be able to give.
>
> kind regards,
>
> Roel Meeuws
> --------------------------------------------
> Roel Meeuws
> PhD. Student
> Delft University of Technology
> Faculty of Electrical Engineering Mathematics and Computer Science
> Computer Engineering Laboratory
> Mekelweg 4, 2628 CD Delft, The Netherlands
> --------------------------------------------
> Email:r.j.meeuws at tudelft.nl <Email%3Ar.j.meeuws at tudelft.nl>
> Office: HB 16.290
> Office phone: +31 (0)15 27 82 165
> Mob. phone: +31 (0)6 10 82 44 01
> --------------------------------------------
>
> ? ? ? ?[[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>


-- 

Max