R help - Oct 2009 - decision trees using the Hellinger distance rather than

Hi, while working with decision trees and unbalanced data, I came across the
use of the Hellinger distance as an alternative to information gain [1,2],
when dealing with skewed data. Does anybody know of R implementations of
this approach to decision trees?

Thanks,

[1] http://www.cse.nd.edu/Reports/2008/TR-2008-06.pdf
[2] http://csmr.ca.sandia.gov/~wpk/slides/wdmda-sem.pdf
-- 
Rajarshi Guha
NIH Chemical Genomics Center

	[[alternative HTML version deleted]]

Do you happen to have a large .Rdata file that is being loaded, or something in
your .Rprofile?  Try searching for a file with that name.  Or start R with a
--vanilla and see if that helps...
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at
r-project.org]
> On Behalf Of Rajarshi Guha
> Sent: Friday, October 02, 2009 10:33 AM
> To: R
> Subject: [R] decision trees using the Hellinger distance rather than
> 
> Hi, while working with decision trees and unbalanced data, I came across
> the
> use of the Hellinger distance as an alternative to information gain [1,2],
> when dealing with skewed data. Does anybody know of R implementations of
> this approach to decision trees?
> 
> Thanks,
> 
> [1] http://www.cse.nd.edu/Reports/2008/TR-2008-06.pdf
> [2] http://csmr.ca.sandia.gov/~wpk/slides/wdmda-sem.pdf
> --
> Rajarshi Guha
> NIH Chemical Genomics Center
> 
> 	[[alternative HTML version deleted]]
> 
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