If performing regression, calculate which outofbag residuals and MSE. Otherwise, calculate which outofbag observations were classified correctly, what the overall misclassification rate is, as well as the confusion matrix.
1  defaultOOBPerformanceAnalysis(prediction, response, oobObs)

prediction 
a vector of predicted responses. 
response 
a vector of true response. 
oobObs 
a vector of indices which values in 
If performing regression, return a list with components:
oobMSE 
the outofbag mean squared error. 
resVec 
a vector of length 
Otherwise, return a list with components:
oobErr 
overall misclassification rate. 
oobConfMat 
the confusion matrix of outofbag predictions against the true class labels. 
errVec 
a vector of length 
Other performance analyzers: boost
,
boost.function
, boost.list
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
All documentation is copyright its authors; we didn't write any of that.