I think you should use 10 fold cross validation to judge your performance on
the validation parts. What you did will be overfitted for sure, you test on
the same training set used for your model buliding.


On Sat, Oct 23, 2010 at 6:39 AM, mxkuhn <mxkuhn@gmail.com> wrote:

> I think the issue is that you really can't use the training set to judge
> this (without resampling).
>
> For example, k nearest neighbors are not known to over fit, but  a 1nn
> model will always perfectly predict the training data.
>
> Max
>
> On Oct 23, 2010, at 9:05 AM, "Liaw, Andy" <andy_liaw@merck.com> wrote:
>
> > What Breiman meant is that as the model gets more complex (i.e., as the
> > number of trees tends to infinity) the geneeralization error (test set
> > error) does not increase.  This does not hold for boosting, for example;
> > i.e., you can't "boost forever", which nececitate the need to find the
> > optimal number of iterations.  You don't need that with RF.
> >
> >> -----Original Message-----
> >> From: r-help-bounces@r-project.org
> >> [mailto:r-help-bounces@r-project.org] On Behalf Of vioravis
> >> Sent: Saturday, October 23, 2010 12:15 AM
> >> To: r-help@r-project.org
> >> Subject: Re: [R] Random Forest AUC
> >>
> >>
> >> Thanks Max and Andy. If the Random Forest is always giving an
> >> AUC of 1, isn't
> >> it over fitting??? If not, how do you differentiate this from over
> >> fitting??? I believe Random forests are claimed to never over
> >> fit (from the
> >> following link).
> >>
> >> http://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.ht<http://www.stat.berkeley.edu/%7Ebreiman/RandomForests/cc_home.ht>
> >> m#features
> >>
> >>
> >> Ravishankar R
> >> --
> >> View this message in context:
> >> http://r.789695.n4.nabble.com/Random-Forest-AUC-tp3006649p3008157.html
> >> Sent from the R help mailing list archive at Nabble.com.
> >>
> >> ______________________________________________
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> >> and provide commented, minimal, self-contained, reproducible code.
> >>
> > Notice:  This e-mail message, together with any attachme...{{dropped:11}}
> >
> > ______________________________________________
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> > and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
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> and provide commented, minimal, self-contained, reproducible code.
>



-- 
Sincerely,
Changbin
--

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