Generally speaking, the pseudo R^2 of 70% is a rather good model (obviously depends on the kind of data you have at hand). Because it's "pseudo", not "real", R^2, so the range is not limited to [0, 100%], but it's hard for me to imagine anyone getting >100%.
You may want to check the distribution of the response (or residuals) to see if a transformation is appropriate. Tree-based methods (of which random forests is one) can be sensitive to heteroscedasticity. Best, Andy From: lara harrup (IAH-P) > > Hi all > > I have been trying to use the randomForest package to model > insect species abundance in different habitats and identify > the key variables (landscape/climate etc) in determining > abundance, which has all worked fine and I get nice variable > importance plots etc. Many thanks to everyone on this help > forum who has given tips/advice along the way. > > But the percentage variance explained /pseudo r squared > reported when I call print(model) is quite low, depending on > the species being modelled it ranges from a maximum of 23.69 > right down to -2.08. > > I believe that the minus value represents a model that > performs no better / worse than random and obviously the > larger the R^2 gets the better the predictive ability but > over what range does this r^2 operate? > > As it is not unexpected that some of these models would have > poor predictive accuracy as part of the larger project around > this work is to say finer resolution remotely sensed > satellite imagery is needed to derive the climate variables > etc being used to predict species abundance. > > My question is probably a bit like how long is a piece of > string but if anyone could offer some guidance on what > constitutes a good / very good / bad / very bad r-squared > value for random forest it would be most appreciated and if > there are any other accuracy measure that can be used with > Random Forest in addition to the pseudo r^2 value? as this > work will be presented to an entomology/ecology audience > where machine learning is a bit outside their (and my) > statistics comfort zone. > > Many thanks in advance > > Lara > > lara.har...@bbsrc.ac.uk > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org 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. > Notice: This e-mail message, together with any attachme...{{dropped:12}} ______________________________________________ R-help@r-project.org 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.