R help - Apr 2010 - Question on implementing Random Forests scoring

So I've been working with Random Forests ( R library is randomForest) and I
curious if Random Forests could be applied to classifying on a real time
basis.  For instance lets say I've scored fraud from a group of
transactions.  If I want to score any new incoming transactions for fraud
could Random Forests be used in that context.  Linear Regression is nice in
that it is very easy to score.

I suppose R could be used as a real time API to load in data, score, then
output results.  Is there any other way with Random Forests?

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From: Larry D'Agostino
> 
> So I've been working with Random Forests ( R library is 
> randomForest) and I
> curious if Random Forests could be applied to classifying on 
> a real time
> basis.  For instance lets say I've scored fraud from a group of
> transactions.  If I want to score any new incoming 
> transactions for fraud
> could Random Forests be used in that context.  Linear 
> Regression is nice in
> that it is very easy to score.
> 
> I suppose R could be used as a real time API to load in data, 
> score, then
> output results.  Is there any other way with Random Forests?
Yes, but not without more work.  You can write the forest out to a file
(with simple R code), and then write a stand-alone C code to read that
model file and score the new data.  The C function that scores new data
from the model can be found in the source code of the package.  Your C
code just need to wrap around that.

Andy
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