Elastic-Net Regression is combines Lasso Regression with Ridge Regression to give you the best of both worlds. It works well when there are lots of useless variables that need to be removed from the equation and it works well when there are lots of useful variables that need to be retained. And it does better than either one when it comes to handling correlated variables. Dang!!!! NOTE: This StatQuest follows up on the the StatQuest on Ridge Regression... https://www.youtube.com/watch?v=Q81RR3yKn30 ...and the StatQuest on Lasso Regression.... https://www.youtube.com/watch?v=NGf0voTMlcs For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ Also, here are some references that helped me put this video together: The original manuscript on Elastic-Net Regression: https://web.stanford.edu/~hastie/Papers/B67.2%20%282005%29%20301-320%20Zou%20&%20Hastie.pdf A webpage at North Carolina State University that shows different situations for Ridge, Lasso and Elastic-Net Regression: https://www4.stat.ncsu.edu/~post/josh/LASSO_Ridge_Elastic_Net_-_Examples.html If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: null ...a cool StatQuest t-shirt or sweatshirt: null ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer #statquest #regularization