bag.aucoob {GPLTR} | R Documentation |
AUC on the Out Of Bag samples
Description
Compute the AUC on the OOB samples of the bagging procedure for the binomial family. The true and false positive rates are also returned and could be helpfull for plotting the ROC curves.
Usage
bag.aucoob(bag_pltr, xdata, Y.name)
Arguments
bag_pltr |
The output of the function |
xdata |
The learning dataset containing the dependent variable, the confounding variables and the predictors variables |
Y.name |
The name of the binary dependent variable |
Details
The thresshold values used for computing the AUC are defined when building the bagging predictor. see bagging.pltr
for the convenient parameterization.
Value
A list of 4 elements
AUCOOB |
the AUC computed on OOB samples of the Bagging procedure |
TPR |
the true positive rate for several thresshold values |
FPR |
the false positive rate for several thresshold values |
OOB |
the Out Of Bag error for each thresshold value |
Note
The plot of the ROC curve is straighforward using the TPR
and FPR
obtained with the function bag.aucoob
Author(s)
Cyprien Mbogning
References
Mbogning, C., Perdry, H., Broet, P.: A Bagged partially linear tree-based regression procedure for prediction and variable selection (submitted 2014)
Examples
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