8 References

Breiman, Leo. 2001. “Random Forests.” Machine Learning 45 (1): 5–32. https://doi.org/10.1023/A:1010933404324.

Brent, Richard P. 1971. “An Algorithm with Guaranteed Convergence for Finding a Zero of a Function.” The Computer Journal 14 (4): 422–25.

Chen, Tianqi, and Carlos Guestrin. 2016. “Xgboost: A Scalable Tree Boosting System.” In Proceedings of the 22nd Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 785–94. https://doi.org/10.1145/2939672.2939785.

Chen, Tianqi, Tong He, Michael Benesty, Vadim Khotilovich, Yuan Tang, Hyunsu Cho, Kailong Chen, et al. 2019. xgboost: Extreme Gradient Boosting. https://CRAN.R-project.org/package=xgboost.

Friedman, Jerome H. 2001. “Greedy Function Approximation: A Gradient Boosting Machine.” Annals of Statistics, 1189–1232. https://doi.org/10.1214/aos/1013203451.

Friedman, Jerome, Trevor Hastie, and Robert Tibshirani. 2010. “Regularization Paths for Generalized Linear Models via Coordinate Descent.” Journal of Statistical Software 33 (1): 1–22. https://doi.org/10.18637/jss.v033.i01.

H2O.ai. 2016. R Interface for H2o. https://github.com/h2oai/h2o-3.

Magaret, Craig A, David C Benkeser, Brian D Williamson, Bhavesh R Borate, Lindsay N Carpp, Ivelin S Georgiev, Ian Setliff, et al. 2019. “Prediction of VRC01 Neutralization Sensitivity by HIV-1 gp160 Sequence Features.” PLoS Computational Biology 15 (4): e1006952. https://doi.org/10.1371/journal.pcbi.1006952.

Polley, Eric, Erin LeDell, Chris Kennedy, and Mark van der Laan. 2019. SuperLearner: Super Learner Prediction. https://CRAN.R-project.org/package=SuperLearner.

Shen, Lin, Susan Peterson, Ahmad R Sedaghat, Moira A McMahon, Marc Callender, Haili Zhang, Yan Zhou, et al. 2008. “Dose-Response Curve Slope Sets Class-Specific Limits on Inhibitory Potential of anti-HIV Drugs.” Nature Medicine 14 (7): 762–66. https://doi.org/10.1038/nm1777.

van der Laan, Mark J, Eric C Polley, and Alan E Hubbard. 2007. “Super Learner.” Statistical Applications in Genetics and Molecular Biology 6 (1). https://doi.org/10.2202/1544-6115.1309.

Wagh, Kshitij, Tanmoy Bhattacharya, Carolyn Williamson, Alex Robles, Madeleine Bayne, Jetta Garrity, Michael Rist, et al. 2016. “Optimal Combinations of Broadly Neutralizing Antibodies for Prevention and Treatment of HIV-1 Clade C Infection.” PLoS Pathogens 12 (3). https://doi.org/10.1371/journal.ppat.1005520.

Williamson, Brian D, Peter B Gilbert, Noah R Simon, and Marco Carone. 2020. “A Unified Approach for Inference on Algorithm-Agnostic Variable Importance.” arXiv Preprint. https://arxiv.org/abs/2004.03683.

Williamson, Brian D., Noah Simon, and Marco Carone. 2020. “vimp: Perform Inference on Algorithm-Agnostic Variable Importance.” https://CRAN.R-project.org/package=vimp.

Wright, Marvin N., and Andreas Ziegler. 2017. “ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R.” Journal of Statistical Software 77 (1): 1–17. https://doi.org/10.18637/jss.v077.i01.

Yoon, Hyejin, Jennifer Macke, Anthony P West Jr, Brian Foley, Pamela J Bjorkman, Bette Korber, and Karina Yusim. 2015. “CATNAP: A Tool to Compile, Analyze and Tally Neutralizing Antibody Panels.” Nucleic Acids Research 43 (W1): W213–W219. https://doi.org/10.1093/nar/gkv404.

Zou, Hui, and Trevor Hastie. 2005. “Regularization and Variable Selection via the Elastic Net.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 67 (2): 301–20. https://doi.org/10.1111/j.1467-9868.2005.00503.x.