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. Author manuscript; available in PMC: 2020 Aug 24.
Published in final edited form as: J Appl Stat. 2019 Feb 22;46(12):2216–2236. doi: 10.1080/02664763.2019.1582614

Table 5.:

Performance as measured by AUC and negative log-likelihood for the three Super Learners with the following libraries: machine learning algorithms with only baseline covariates, augmenting this library with hdPS, and only the machine learning algorithms but with both baseline and hdPS screened covariates. (See Table 1).

Data set Performance Metric Super Learner 1 Super Learner2 Super Learner 3
NOAC AUC 0.7652 0.8203 0.8304
NSAID 0.6651 0.6967 0.6975
VYTORIN 0.6931 0.6970 0.698
NOAC Negative Log-likelihood 0.5251 0.4808 0.4641
NSAID 0.6099 0.5939 0.5924
VYTORIN 0.4191 0.4180 0.4171