Timeline for Residual plot for regression tree: What should it look like?

3 events

when toggle format	what		by	license	comment
Apr 27, 2014 at 23:49	comment	added	Bruno		I was not relying on a Markovian assumption. I thought that the regression tree makes cuts to reduce the squared error within the groups. The best way to do this is to predict at the mean of the group, which would imply residuals centered at 0. That's why I asked if these were weighted or if some of the points were not visible on the plot. I am intrigued, I'll think about it some more, but do throw a hint!
Apr 27, 2014 at 18:56	comment	added	user44450		Your first comment makes a lot of sense, it's essentially a family of linear functions for each prediction p. For your second question , that is the training set. You would expect the residuals to be centered around zero only as a Markov assumption for linear regression, but no distribution is assumed for regression trees. I think if you use your logic in the first comment it helps to see why the second plot is the way it is...
Apr 26, 2014 at 3:17	history	answered	Bruno	CC BY-SA 3.0