aucs: Sets the performance metric to be area under the AUC and PR...
In novasmedley/gbmSpm: Find predictive sequential patterns for clinical glioblastoma patients
Description
Usage
Details
Value
Examples
Description
Sets the performance metric to be area under the AUC and PR curve
Usage
1
Details
Modifies summaryFunction used in trainControl.
Creates additional summary functions for summaryFunction.
Possible methods for evaluating cross-validation performance in trainControl
can then be prAUC or rocAUC for area under the precision-recall curve
and area under the ROC curve, respectively.
Their performance names are found in getPerformanceNames.
Value
named vector of two functions: prAUC or rocAUC
Examples
1
2
# not run
trainControl(method='cv', classProbs=T, index = index, summaryFunction=aucs)
novasmedley/gbmSpm documentation built on May 17, 2019, 10:39 a.m.
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Description Usage Details Value Examples
Description
Sets the performance metric to be area under the AUC and PR curve
Usage
1 |
Details
Modifies summaryFunction used in trainControl.
Creates additional summary functions for summaryFunction.
Possible methods for evaluating cross-validation performance in trainControl
can then be prAUC or rocAUC for area under the precision-recall curve
and area under the ROC curve, respectively.
Their performance names are found in getPerformanceNames.
Value
named vector of two functions: prAUC or rocAUC
Examples
1 2 | # not run
trainControl(method='cv', classProbs=T, index = index, summaryFunction=aucs)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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