[BioC] what metric is used to evalute the error rate?

Weiwei Shi helprhelp at gmail.com
Tue Nov 21 22:56:30 CET 2006

Hi, there:

This is a question a little bit off topic but I believe many people
using bioconductor might have this situation so I ask it here and hope
I can get some suggestion.

I have a result which looks like this:
     net num.genes overall.error overall.pred.error
1 custom         5       0.15625 0.05263

The overall.error is (b+c)/(a+b+c+d) from cross-validation for
training data; while the overall.pred.error is the one for test data.
Since the sample sizes of training and test data are different, it
gives me the result which performs better in test than training. I am
wondering if there are some other metrics to evalute this
classification error rate so that it can consider the effects of
sample size.


Weiwei Shi, Ph.D
Research Scientist
GeneGO, Inc.

"Did you always know?"
"No, I did not. But I believed..."
---Matrix III

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