Decision Trees and Boosting, XGBoost | Two Minute Papers #55

A decision tree is a great tool to help making good decisions from a huge bunch of data. In this episode, we talk about boosting, a technique to combine a lot of weak decision trees into a strong learning algorithm. Please note that gradient boosting is a broad concept and this is only one possible application of it! __________________________________ Our Patreon page is available here: https://www.patreon.com/TwoMinutePapers If you don't want to spend a dime or you can't afford it, it's completely okay, I'm very happy to have you around! And please, stay with us and let's continue our journey of science together! The paper "Experiments with a new boosting algorithm" is available here: http://www.public.asu.edu/~jye02/CLASSES/Fall-2005/PAPERS/boosting-icml.pdf Another great introduction to tree boosting: http://homes.cs.washington.edu/~tqchen/pdf/BoostedTree.pdf WE WOULD LIKE TO THANK OUR GENEROUS SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Sunil Kim, Vinay S. The thumbnail image background was created by John Voo (CC BY 2.0), content-aware filling has been applied - https://flic.kr/p/BLphju Splash screen/thumbnail design: Felícia Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Patreon → https://www.patreon.com/TwoMinutePapers Facebook → https://www.facebook.com/TwoMinutePap... Twitter → https://twitter.com/karoly_zsolnai Web → https://cg.tuwien.ac.at/~zsolnai/