Changbin, The weights don't have to sum up to one. These are the weights of the trees in the bag used to combine them into the final fit, and if I'm not mistaken expressed as the logit of the error for the respective trees.
If you use a method, be sure you understand it. If you don't understand those weights, I reckon there's a whole lot of other things you don't understand about the method. A good start is running and analyzing the example in the help file. Those weights don't sum up to one either, but the authors don't seem to mind... There are references given in the help files, and you should understand what they say before you apply the algorithm. You're not going to handle a chainsaw without reading the manual carefully either. Cheers Joris On Sat, Jun 19, 2010 at 11:35 PM, Changbin Du <changb...@gmail.com> wrote: > HI, Guys, > > I am trying to use the AdaBoosting. M.1 algorithm to integrate three models. > I found the sum of weights for each model is not equal to one. > > How to deal with this? > > Thanks, any response or suggestions are appreciated! > > > -- > Sincerely, > Changbin > -- > > [[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. > -- Joris Meys Statistical consultant Ghent University Faculty of Bioscience Engineering Department of Applied mathematics, biometrics and process control tel : +32 9 264 59 87 joris.m...@ugent.be ------------------------------- Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php ______________________________________________ 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.
