Question: what metric is used to evalute the error rate?
0
gravatar for Weiwei Shi
12.8 years ago by
Weiwei Shi1.2k
Weiwei Shi1.2k wrote:
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. thanks -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc. "Did you always know?" "No, I did not. But I believed..." ---Matrix III
• 342 views
ADD COMMENTlink modified 12.8 years ago by Kevin R. Coombes140 • written 12.8 years ago by Weiwei Shi1.2k
Answer: what metric is used to evalute the error rate?
0
gravatar for Kevin R. Coombes
12.8 years ago by
Kevin R. Coombes140 wrote:
Shouldn't there be error bars (i.e., confidence intervals) around those error estimates, that ought to get smaller when you use more samples? Best, Kevin Weiwei Shi wrote: > 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. > > thanks >
ADD COMMENTlink written 12.8 years ago by Kevin R. Coombes140
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 16.09
Traffic: 180 users visited in the last hour