[R] pseudo-R2 or GOF for regression trees?

2007-05-05 Thread Prof. Jeffrey Cardille
Hello,

Is there an accepted way to convey, for regression trees, something  
akin to R-squared?

I'm developing regression trees for a continuous y variable and I'd  
like to say how well they are doing. In particular, I'm analyzing the  
results of a simulation model having highly non-linear behavior, and  
asking what characteristics of the inputs are related to a particular  
output measure.  I've got a very large number of points: n=4000.  I'm  
not able to do a model sensitivity analysis because of the large  
number of inputs and the model run time.

I've been googling around both on the archives and on the rest of the  
web for several hours, but I'm still having trouble getting a firm  
sense of the state of the art.  Could someone help me to quickly  
understand what strategy, if any, is acceptable to say something like  
The regression tree in Figure 3 captures 42% of the variance?  The  
target audience is readers who will be interested in the subsequent  
verbal explanation of the relationship, but only once they are  
comfortable that the tree really does capture something.  I've run  
across methods to say how well a tree does relative to a set of trees  
on the same data, but that doesn't help much unless I'm sure the  
trees in question are really capturing the essence of the system.

I'm happy to be pointed to a web site or to a thread I may have  
missed that answers this exact question.

Thanks very much,

Jeff

--
Prof. Jeffrey Cardille
[EMAIL PROTECTED]

 

**  Département de Géographie   **  
Bureau: **
**  professeur adjoint / assistant professor**  
Salle 440   **
**  Université de Montréal  **  
Pavillon Strathcona **
**  C.P. 6128   
**  520, chemin de la Côte-Ste-Catherine**
**  Succursale Centre-ville **  
Montreal, QC H2V 2B8**
**  Montréal, QC, H3C 3J7   **  
Télé: (514) 343-8003**
 

**  Web:
**
**  http://www.geog.umontreal.ca/geog/cardille.htm  **
**  
**
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[R] pseudo-R2 or GOF for regression trees?

2007-05-05 Thread Prof. Jeffrey Cardille

All-- Apologies if I have inadvertently posted this message twice; I  
just joined the list today, after trying to post once.

Thanks-
Jeff

# r-help message is below #

Hello,

Is there an accepted way to convey, for regression trees, something  
akin to R-squared?

I'm developing regression trees for a continuous y variable and I'd  
like to say how well they are doing. In particular, I'm analyzing the  
results of a simulation model having highly non-linear behavior, and  
asking what characteristics of the inputs are related to a particular  
output measure.  I've got a very large number of points: n=4000.  I'm  
not able to do a model sensitivity analysis because of the large  
number of inputs and the model run time.

I've been googling around both on the archives and on the rest of the  
web for several hours, but I'm still having trouble getting a firm  
sense of the state of the art.  Could someone help me to quickly  
understand what strategy, if any, is acceptable to say something like  
The regression tree in Figure 3 captures 42% of the variance?  The  
target audience is readers who will be interested in the subsequent  
verbal explanation of the relationship, but only once they are  
comfortable that the tree really does capture something.  I've run  
across methods to say how well a tree does relative to a set of trees  
on the same data, but that doesn't help much unless I'm sure the  
trees in question are really capturing the essence of the system.

I'm happy to be pointed to a web site or to a thread I may have  
missed that answers this exact question.  I've seen similar postings  
but nothing that's an unequivocal answer any help would be  
greatly appreciated!

Thanks very much,

Jeff

--
Prof. Jeffrey Cardille
[EMAIL PROTECTED]

 

**  Département de Géographie   **  
Bureau: **
**  professeur adjoint / assistant professor**  
Salle 440   **
**  Université de Montréal  **  
Pavillon Strathcona **
**  C.P. 6128   
**  520, chemin de la Côte-Ste-Catherine**
**  Succursale Centre-ville **  
Montreal, QC H2V 2B8**
**  Montréal, QC, H3C 3J7   **  
Télé: (514) 343-8003**
 

**  Web:
**
**  http://www.geog.umontreal.ca/geog/cardille.htm  **
**  
**
**  Calendrier de Disponibilité à:  
**
**  http://jeffcardille.googlepages.com/udem**






[[alternative HTML version deleted]]

__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.