Displaying 1 result from an estimated 1 matches for "treetune".
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retune
2011 Dec 31
1
Cross-validation error with tune and with rpart
...3088 0.4768 0.02417800
10 0.00480000 25 0.2448 0.4672 0.02400673
If I got it right, "xerror" stands for the cross-validation error (using
10-fold by default), this is pretty high (0.4672 over 1). However, if I do
something similar using tune from e1071 I get a much lower error:
treetune <- tune(rpart, y~., data=data.frame(xsel, y), predict.func =
treeClassPrediction, cp=0.0048)
> treetune$best.performance[1] 0.2243049
I'm also assuming that the performance returned by "tune" is the
cross-validation error (also 10-fold by default). So where does this
enormous...