XGBoost Part 2 (of 4): Classification скачать в хорошем качестве

XGBoost Part 2 (of 4): Classification

In this video we pick up where we left off in part 1 and cover how XGBoost trees are built for Classification. NOTE: This StatQuest assumes that you are already familiar with... XGBoost Part 1: XGBoost Trees for Regression:    • XGBoost Part 1 (of 4): Regression   ...the main ideas behind Gradient Boost for Classification:    • Gradient Boost Part 3 (of 4): Classification   ...Odds and Log(odds):    • Odds and Log(Odds), Clearly Explained!!!   ...and how the Logistic Function works:    • Logistic Regression Details Pt 2: Maximum ...   Also note, this StatQuest is based on the following sources: The original XGBoost manuscript: https://arxiv.org/pdf/1603.02754.pdf The original XGBoost presentation: https://homes.cs.washington.edu/~tqch... And the XGBoost Documentation: https://xgboost.readthedocs.io/en/lat... For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Patreon:   / statquest   ...or... YouTube Membership:    / @statquest   ...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...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:   / joshuastarmer   Corrections: 14:24 I meant to say "larger" instead of "lower. 18:48 In the original XGBoost documents they use the epsilon symbol to refer to the learning rate, but in the actual implementation, this is controlled via the "eta" parameter. So, I guess to be consistent with the original documentation, I made the same mistake! :) #statquest #xgboost