Hi, I am working with CART regression now. Could anyone tell me in which cases it is better to use mean square error for splitting nodes and when mean absolute error should be preferred. I am now using the default (MSE) version and I can see that the obtained optimal tree is very different from the tree with the least mean absolute error.
Thanks in advance, Luba -- View this message in context: http://www.nabble.com/regression-trees%3A-mean-square-vs.-absolute-errors-tp16274094p16274094.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
