Hi,
I have a question of classification on imbalanced dataset. I am
wondering if there is a package which can solve this problem via
sampling approach, like one-sided selection.

A follow-up question is, how to select those 'representative' samples
and remove noise/borderlines and redundancy in order to increase
classification accuracy. Is there any work which has been implemented
in R or some GNU softwares?

Thanks,

weiwei



--
Weiwei Shi, Ph.D

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

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