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 <[EMAIL PROTECTED]> wrote: > Random forest can do the job. > > HTH. > > On 8/3/05, Weiwei Shi <[EMAIL PROTECTED]> 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 > > > > ______________________________________________ > > [email protected] 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 ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
