[R] question about regression forest

From: Jose Cortinas <jose.cortinas_at_uhasselt.be>
Date: Wed 03 Jan 2007 - 12:57:07 GMT


Dear All,

My name is José Cortiñas Abrahantes, I am statistician and work at the university in Belgium. I started working recently with machine learning techniques and I finding a fascinating field. The reason of my email is to ask you a question related to regression forest. I am interested to compare the fit of linear regression, regression trees, bagging trees and regression forest for the case in which we have only one predictor variable. In all the articles that I have found related to regression forest they reported the advantages of the use of a random subsets of predictors used to grow the tree with respect to bagging, in my case I have only one, thus it is not really contributing. I was
expecting then to see a similar behaviour than bagging, the rsquared values produced by both methods are very similar indeed, but what I find strange is that if I take the 2.5 and 97.5 percentile of all rsquared from each tree grow the interval obtained for regression forest is much narrower than the one obtained for bagging. Do anyone know why is this? Thanks in advance.

Best regards and best wishes for 2007,
José Cortiñas Abrahantes



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