Machine learning with imbalanced classification

@spaul wrote:

I have an outcome variable with three levels, one of which only 9% of my sample belongs to. Is that too low? Do techniques such as bagging or boosting inherently account for this distribution in the algorithm? I’ve read that using kappa instead of accuracy as the metric with which to evaluate the model may be a good idea?

Thank you!!

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