thanks for your help. maybe I have poor statistics level, I can not well understand your means.
wishes kevin<br><br>å¨2010-05-11ï¼"Bert Gunter" <gunter.ber...@gene.com> åéï¼ >(Near) non-identifiability (especially in nonlinear models, which include >linear mixed effects models, Bayesian hierarchical models, etc.) is >typically a strong clue; usually indicated by software complaints (e.g. >convergence failures, running up against iteration limits, etc.). > >However this is sufficient-ish, not necessary: "over-fitting" frequently >occurs even without such overt complaints. It should also be said that, >except for identifiability, "over-fitting" is not a well-defined >statistical term: it depends on the scientific context. > > >Bert Gunter >Genentech Nonclinical Biostatistics > > -----Original Message----- >From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On >Behalf Of Steve Lianoglou >Sent: Sunday, May 09, 2010 6:13 PM >To: David Winsemius >Cc: r-help@r-project.org; bbslover >Subject: Re: [R] How to estimate whether overfitting? > >On Sun, May 9, 2010 at 11:53 AM, David Winsemius <dwinsem...@comcast.net> >wrote: >> >> On May 9, 2010, at 9:20 AM, bbslover wrote: >> >>> >>> 1. is there some criterion to estimate overfitting?  e.g. R2 and Q2 in >the >>> training set, as well as R2 in the test set, when means overfitting.  >for >>> example,  in my data, I have R2=0.94 for the training set and  for the >>> test >>> set R2=0.70, is overfitting? >>> 2. in this scatter, can one say this overfitting? >>> >>> 3. my result is obtained by svm, and the sample are 156 and 52 for the >>> training and test sets, and predictors are 96,  In this case, can svm be >>> employed to perform prediction?  whether the number of the predictors >are >>> too many ? >>> >> >> I think you need to buy a copy of Hastie, Tibshirani, and Friedman and do >> some self-study of chapters 7 and 12. > >And you don't even have to buy it before you can start studying since >the PDF is available here: >http://www-stat.stanford.edu/~tibs/ElemStatLearn/ > >Having a hard cover is always handy, tho .. >-steve > >-- >Steve Lianoglou >Graduate Student: Computational Systems Biology > | Memorial Sloan-Kettering Cancer Center > | Weill Medical College of Cornell University >Contact Info: http://cbio.mskcc.org/~lianos/contact > >______________________________________________ >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]]
______________________________________________ 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.
