Yes, rpart.control() has a bunch of parameters...
I don't know which one can mostly improve the classification performance.


On 3/9/06, Carlos Ortega <[EMAIL PROTECTED]> wrote:
>
>  Hello,
>
> Yes, check rpart.control() for details.
>
> Regards,
>  Carlos.
>
>
>  On 3/9/06, Michael <[EMAIL PROTECTED]> wrote:
> >
> > I see! So you mean I have to collect error counts myself manually...
> >
> > By the way, what parameters do I normally change to improve the default
> > rpart performance?
> >
> > Thanks a lot!
> >
> >
> > On 3/8/06, Carlos Ortega <[EMAIL PROTECTED]> wrote:
> > >
> > > Hello Michael,
> > >
> > > In some of the examples in the rpart function you will find that
> > > comparison between the actual and the predicted values, although it is for
> > > the "Classification" mode, not for the regression.
> > >
> > > Regards,
> > > Carlos.
> > >
> > >
> > >  On 3/7/06, Michael < [EMAIL PROTECTED] > wrote:
> > >
> > > > Hi all,
> > > >
> > > >
> > > >
> > > > What parameter do I normally change in the rpart function? How do I
> > > > set the
> > > > "cp" option?
> > > >
> > > >
> > > >
> > > > Is there a way to read off error rate directly from the "rpart"
> > > > function for
> > > > training data; I imagine for testing data I have to apply a
> > > > "predict", but
> > > > for training data I guess the error count would be somewhere
> > > > existing once
> > > > the "rpart" function is finished. Looks like it is related to
> > > > expressions
> > > > such as "expected loss=0.8362365" when using "summary" function.
> > > >
> > > > Now I have to do this manually, and when it came to compare the
> > > > correct vs.
> > > > wrong and count the errors, it was always very tedious...
> > > >
> > > >
> > > >
> > > > Thanks a lot!
> > > >
> > > >
> > > >
> > > > M.
> > > >
> > > >        [[alternative HTML version deleted]]
> > > >
> > > > ______________________________________________
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> > > > PLEASE do read the posting guide!
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> > > >
> > >
> > >
> >
>

        [[alternative HTML version deleted]]

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