one_boot_auc: Internal function used to perform one bootstrap sample. The...
In nlpred: Estimators of Non-Linear Cross-Validated Risks Optimized for Small Samples
Description
Usage
Arguments
Value
View source: R/auc_functions.R
Description
Internal function used to perform one bootstrap sample. The function
trys to fit learner on a bootstrap sample. If for some reason
(e.g., the bootstrap sample contains no observations with Y = 1)
the learner fails, then the function returns NA. These NAs
are ignored later when computing the bootstrap corrected estimate.
Usage
1
one_boot_auc(Y, X, n, correct632, learner)
Arguments
Y
A numeric binary outcome
X
A data.frame of variables for prediction.
n
Number of observations
correct632
A boolean indicating whether to use the .632 correction.
learner
A wrapper that implements the desired method for building a
prediction algorithm. See ?glm_wrapper or read the package vignette
for more information on formatting learners.
Value
If learner executes successfully, a numeric estimate of AUC
on this bootstrap sample. Otherwise the function returns NA.
nlpred documentation built on Feb. 24, 2020, 1:11 a.m.
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Description Usage Arguments Value
View source: R/auc_functions.R
Description
Internal function used to perform one bootstrap sample. The function
trys to fit learner on a bootstrap sample. If for some reason
(e.g., the bootstrap sample contains no observations with Y = 1)
the learner fails, then the function returns NA. These NAs
are ignored later when computing the bootstrap corrected estimate.
Usage
1 | one_boot_auc(Y, X, n, correct632, learner)
|
Arguments
Y |
A numeric binary outcome |
X |
A |
n |
Number of observations |
correct632 |
A boolean indicating whether to use the .632 correction. |
learner |
A wrapper that implements the desired method for building a
prediction algorithm. See |
Value
If learner executes successfully, a numeric estimate of AUC
on this bootstrap sample. Otherwise the function returns NA.
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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