Thanks.
I knew rf based on proximity can detect the outlier but when the data
size goes to 1 million and the features go around 200, I guess I
probably do not have enough memory to proceed. Do u have some
experience of outlier detection in this kind of data size?
regards,
weiwei
On 8/3/05, Wensui Liu <liuwensui at gmail.com>
wrote:> Random forest can do the job.
>
> HTH.
>
> On 8/3/05, Weiwei Shi <helprhelp at gmail.com> wrote:
> > Hi, there:
> > I am wondering what packages are available in R which can do
"outlier
> > detection" in large-scale dataset.
> >
> > Thanks for sharing info,
> >
> > weiwei
> >
> > --
> > Weiwei Shi, Ph.D
> >
> > "Did you always know?"
> > "No, I did not. But I believed..."
> > ---Matrix III
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
> >
>
>
> --
> WenSui Liu, MS MA
> Senior Decision Support Analyst
> Division of Health Policy and Clinical Effectiveness
> Cincinnati Children Hospital Medical Center
>
--
Weiwei Shi, Ph.D
"Did you always know?"
"No, I did not. But I believed..."
---Matrix III