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
--------------------------------------------

	[[alternative HTML version deleted]]

