Hi,
I have done an analysis using 'rpart' to construct a Classification Tree. I
am wanting to retain the output in tree form so that it is easily
interpretable. However, I am wanting to compare the 'accuracy' of the tree
to a Random Forest to estimate how much predictive ability is lost by using
one simple tree. My understanding is that the error automatically displayed
by the two functions is calculated differently so it is therefore incorrect
to use this as a comparison. Instead I have produced a table for both
analyses comparing the observed and predicted response.
E.g. table(data$dependent,predict(model,type="class"))
I am looking for confirmation that (a) it is incorrect to compare the error
estimates for the two techniques and (b) that comparing the
misclassification rates is an appropriate method for comparing the two
techniques.
Thanks
Amy
Amelia Koch
University of Tasmania
School of Geography and Environmental Studies
Private Bag 78 Hobart
Tasmania, Australia 7001
Ph: +61 3 6226 7454
[EMAIL PROTECTED]
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