tmp_method.CC_nloglik: Temporary fix for convex combination method negative...
In benkeser/drtmle: Doubly-Robust Nonparametric Estimation and Inference
tmp_method.CC_nloglik R Documentation
Temporary fix for convex combination method negative log-likelihood loss
Relative to existing implementation, we reduce the tolerance at which
we declare predictions from a given algorithm the same as another.
Note that because of the way SuperLearner is structure, one needs to
install the optimization software separately.
Description
Temporary fix for convex combination method negative log-likelihood loss
Relative to existing implementation, we reduce the tolerance at which
we declare predictions from a given algorithm the same as another.
Note that because of the way SuperLearner is structure, one needs to
install the optimization software separately.
Usage
tmp_method.CC_nloglik()
benkeser/drtmle documentation built on Jan. 6, 2023, 11:40 a.m.
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| tmp_method.CC_nloglik | R Documentation |
Temporary fix for convex combination method negative log-likelihood loss
Relative to existing implementation, we reduce the tolerance at which
we declare predictions from a given algorithm the same as another.
Note that because of the way SuperLearner is structure, one needs to
install the optimization software separately.
Description
Temporary fix for convex combination method negative log-likelihood loss
Relative to existing implementation, we reduce the tolerance at which
we declare predictions from a given algorithm the same as another.
Note that because of the way SuperLearner is structure, one needs to
install the optimization software separately.
Usage
tmp_method.CC_nloglik()
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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