18 References
Burkov, Andriy. 2019. The Hundred-Page Machine Learning Book. http://themlbook.com/
Goldburd, Mark et al. 2016.Generalized Linear Models for Insurance Rating: CAS Monograph Series Number 5. https://contentpreview.s3.us-east-2.amazonaws.com/CAS+Monograph+5+-+Generalized+Linear+Models+for+Insurance+Ratemaking.pdf
Hastie, Trevor, et al. 2002. The Elements of Statistical Learning. Print.
James, Gareth, et al. 2017. An Introduction to Statistical Learning. http://faculty.marshall.usc.edu/gareth-james/ISL/ISLR%20Seventh%20Printing.pdf
Piech, Chris and Ng, Andrew. 2019. Stanford CS221. Course Notes. https://stanford.edu/~cpiech/cs221/handouts/kmeans.html
Rigollet, Philippe (2017). Lecture 21: Generalized Linear Models. Video. https://www.youtube.com/watch?v=X-ix97pw0xY&t=899s
Wickham, Hadley. 2019. R for Data Science. https://r4ds.had.co.nz/
“Complimentary Log Log Model.” University of Alberta. Accessed 2020. http://www.stat.ualberta.ca/~kcarrier/STAT562/comp_log_log.pdf
The examples of the Ridge and Lasso are an adaptation of p. 251-255 of “Introduction to
Statistical Learning with Applications in R” by Gareth James, Daniela Witten, Trevor Hastie and Robert
Tibshirani. Adapted by R. Jordan Crouser at Smith College for SDS293: Machine Learning (Spring 2016), and re-implemented in Fall 2016 in tidyverse format by Amelia McNamara and R. Jordan Crouser at Smith College.
Used with permission from Jordan Crouser at Smith College. Additional Thanks to the following contributors on github:
- github.com/jcrouser
- github.com/AmeliaMN
- github.com/mhusseinmidd
- github.com/rudeboybert
- github.com/ijlyttle