On 05/09/2010 10:53 AM, David Winsemius 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 ?
Your test sample is too small by a factor of 100 for split sample
validation to work well.
Frank
I think you need to buy a copy of Hastie, Tibshirani, and Friedman and
do some self-study of chapters 7 and 12.
4.from this picture, can you give me some suggestion to improve model
performance？ and is the picture bad?
5. the picture and data below.
thank you!
http://n4.nabble.com/file/n2164417/scatter.jpg scatter.jpg
http://n4.nabble.com/file/n2164417/pkc-svm.txt pkc-svm.txt
--
--
Frank E Harrell Jr Professor and Chairman School of Medicine
Department of Biostatistics Vanderbilt University
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