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 <dshin@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]]