cutoff.calc: Cutoff Calculation for binary class predictions
In SkadiEye/ITRlearn: Individualized Treatment Rule Learning
Description
Usage
Arguments
Value
Description
Cutoff Calculation for binary class predictions via different ways.
Usage
1
cutoff.calc(cutoff, trainObj = NULL, modelObj = NULL)
Arguments
cutoff
If it's a number between 0 and 1, return this number.
If cutoff == 'prevalence', the prevalence of the first class will be returned.
if cutoff == 'optimal', the cutoff will be optimized by maximizing AUC using the training set.
trainObj
A wClsObj object.
modelObj
A wcls object.
Value
A numeric value as the cutoff
SkadiEye/ITRlearn documentation built on May 24, 2019, 1:31 a.m.
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Description Usage Arguments Value
Description
Cutoff Calculation for binary class predictions via different ways.
Usage
1 | cutoff.calc(cutoff, trainObj = NULL, modelObj = NULL)
|
Arguments
cutoff |
If it's a number between 0 and 1, return this number. If cutoff == 'prevalence', the prevalence of the first class will be returned. if cutoff == 'optimal', the cutoff will be optimized by maximizing AUC using the training set. |
trainObj |
A |
modelObj |
A |
Value
A numeric value as the cutoff
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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