amy, without looking at your actual code, i would suggest you to take a look at rpart.control()
On 2/27/07, Amy Uhrin <[EMAIL PROTECTED]> wrote: > Is there an optimal / minimum sample size for attempting to construct a > classification tree using /rpart/? > > I have 27 seagrass disturbance sites (boat groundings) that have been > monitored for a number of years. The monitoring protocol for each site > is identical. From the monitoring data, I am able to determine the > level of recovery that each site has experienced. Recovery is our > categorical dependent variable with values of none, low, medium, high > which are based upon percent seagrass regrowth into the injury over > time. I wish to be able to predict the level of recovery of future > vessel grounding sites based upon a number of categorical / continuous > predictor variables used here including (but not limited to) such > parameters as: sediment grain size, wave exposure, original size > (volume) of the injury, injury age, injury location. > > When I run /rpart/, the data is split into only two terminal nodes based > solely upon values of the original volume of each injury. No other > predictor variables are considered, even though I have included about > six of them in the model. When I remove volume from the model the same > thing happens but with injury area - two terminal nodes are formed based > upon area values and no other variables appear. I was hoping that this > was a programming issue, me being a newbie and all, but I really think > I've got the code right. Now I am beginning to wonder if my N is too > small for this method? > > -- > Amy V. Uhrin, Research Ecologist > > NOAA, National Ocean Service > Center for Coastal Fisheries and Habitat Research > 101 Pivers Island Road > Beaufort, NC 28516 > (252) 728-8778 > (252) 728-8784 (fax) > [EMAIL PROTECTED] > > ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ > \!/ \!/ <:}}}}}>< \!/ \!/ >^<**>^< \!/ \!/ > > > [[alternative HTML version deleted]] > > ______________________________________________ > [email protected] 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. > -- WenSui Liu A lousy statistician who happens to know a little programming (http://spaces.msn.com/statcompute/blog) ______________________________________________ [email protected] 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.
