Hi, In the R-Help history there have been similar questions to yours. As a starting point you can check this:
http://tolstoy.newcastle.edu.au/R/e2/help/07/01/9138.html Regrads, Carlos. On Thu, Jul 22, 2010 at 6:37 PM, David Shin <ds...@jumptrading.com> wrote: > I'd like to train a decision tree on a set of weighted data points. I > looked into the rpart package, which builds trees but doesn't seem to offer > the capability of weighting inputs. (There is a weights parameter, but it > seems to correspond to output classes rather than to input points). > > I'm making do for now by preprocessing my input data by adding multiple > instances of each data point corresponding to its weight before feeding to > rpart. But I worry this tricks the cross-validation phase of the rpart > building process into thinking a model generalizes better than it really > does. This is because a heavily-weighted point can be included in both the > training and testing set of a cross validation split. > > Is there a better way to achieve my goal? > > ________________________________ > Note: This email is for the confidential use of the named addressee(s) only > and may contain proprietary, confidential or privileged information. If you > are not the intended recipient, you are hereby notified that any review, > dissemination or copying of this email is strictly prohibited, and to please > notify the sender immediately and destroy this email and any attachments. > Email transmission cannot be guaranteed to be secure or error-free. Jump > Trading, therefore, does not make any guarantees as to the completeness or > accuracy of this email or any attachments. This email is for informational > purposes only and does not constitute a recommendation, offer, request or > solicitation of any kind to buy, sell, subscribe, redeem or perform any type > of transaction of a financial product. > > [[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. > [[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.
