Hello all,
I am currently working with rpart to classify vegetation types by spectral
characteristics, and am comming up with poor classifications based on the fact
that I have some vegetation types that have only 15 observations, while others
have over 100. I have attempted to supply prior weights to the dataset, though
this does not improve the classification greatly. Could anyone supply some
hints about how to improve a classification for a badly unbalanced datase?

Thank you,
Helen Mills Poulos

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