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

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 ** ** ** ** 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.

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

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.