References

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Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. 2017. The Elements of Statistical Learning. 2nd ed. New York, NY: Springer. https://web.stanford.edu/~hastie/ElemStatLearn/.

James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2013. An Introduction to Statistical Learning: With Applications in R. 1st ed. New York, NY: Springer. http://faculty.marshall.usc.edu/gareth-james/ISL/book.html.

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Molnar, Christoph. 2020. Interpretable Machine Learning. https://christophm.github.io/interpretable-ml-book/.

Moore, Dirk F. 2016. Applied Survival Analysis Using R. 1st ed. New York, NY: Springer. https://eohsi.rutgers.edu/eohsi-directory/name/dirk-moore/.

Therneau, Terry, and Elizabeth Atkinson. 2019. An Introduction to Recursive Partitioning Using the Rpart Routines. Boca Raton, Florida: Chapman; Hall/CRC. https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf.

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Xie, Yihui. 2019. Bookdown: Authoring Books and Technical Documents with R Markdown. 1st ed. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/bookdown/.

Xie, Yihui, J. J. Allaire, and Garrett Grolemund. 2019. R Markdown: The Definitive Guide. 1st ed. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown/.