AdaBoost is one of those machine learning methods that seems so much more confusing than it really is. It's really just a simple twist on decision trees and random forests.⭐ NOTE: When I code, I use Kite, a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I love it! https://www.kite.com/get-kite/?utm_me...NOTE: This video assumes you already know about Decision Trees...https://youtu.be/_L39rN6gz7Y...and Random Forests....https://youtu.be/J4Wdy0Wc_xQFor a complete index of all the StatQuest videos, check out:https://statquest.org/video-index/Sources:The original AdaBoost paper by Robert E. Schapire and Yoav Freundhttps://www.sciencedirect.com/science...And a follow up by co-created Schapire:http://rob.schapire.net/papers/explai...The idea of using the weights to resample the original dataset comes from Boosting Foundations and Algorithms, by Robert E. Schapire and Yoav Freundhttps://mitpress.mit.edu/books/boostingLastly, Chris McCormick's tutorial was super helpful:http://mccormickml.com/2013/12/13/ada...If you'd like to support StatQuest, please consider...Patreon: https://www.patreon.com/statquest...or...YouTube Membership: https://www.youtube.com/channel/UCtYL......a cool StatQuest t-shirt or sweatshirt (USA/Europe): https://teespring.com/stores/statquest(everywhere):https://www.redbubble.com/people/star......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/statquestLastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:https://twitter.com/joshuastarmer0:00 Awesome song and introduction0:56 The three main ideas behind AdaBoost3:30 Review of the three main ideas3:58 Building a stump with the GINI index6:27 Determining the Amount of Say for a stump10:45 Updating sample weights14:47 Normalizing the sample weights15:32 Using the normalized weights to make the second stump19:06 Using stumps to make classifications19:51 Review of the three main ideas behind AdaBoost#statquest#adaboost
AdaBoost is one of those machine learning methods that seems so much more confusing than it really is. It's really just a simple twist on decision trees and random forests.⭐ NOTE: When I code, I use Kite, a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I love it! https://www.kite.com/get-kite/?utm_me...NOTE: This video assumes you already know about Decision Trees...https://youtu.be/_L39rN6gz7Y...and Random Forests....https://youtu.be/J4Wdy0Wc_xQFor a complete index of all the StatQuest videos, check out:https://statquest.org/video-index/Sources:The original AdaBoost paper by Robert E. Schapire and Yoav Freundhttps://www.sciencedirect.com/science...And a follow up by co-created Schapire:http://rob.schapire.net/papers/explai...The idea of using the weights to resample the original dataset comes from Boosting Foundations and Algorithms, by Robert E. Schapire and Yoav Freundhttps://mitpress.mit.edu/books/boostingLastly, Chris McCormick's tutorial was super helpful:http://mccormickml.com/2013/12/13/ada...If you'd like to support StatQuest, please consider...Patreon: https://www.patreon.com/statquest...or...YouTube Membership: https://www.youtube.com/channel/UCtYL......a cool StatQuest t-shirt or sweatshirt (USA/Europe): https://teespring.com/stores/statquest(everywhere):https://www.redbubble.com/people/star......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/statquestLastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:https://twitter.com/joshuastarmer0:00 Awesome song and introduction0:56 The three main ideas behind AdaBoost3:30 Review of the three main ideas3:58 Building a stump with the GINI index6:27 Determining the Amount of Say for a stump10:45 Updating sample weights14:47 Normalizing the sample weights15:32 Using the normalized weights to make the second stump19:06 Using stumps to make classifications19:51 Review of the three main ideas behind AdaBoost#statquest#adaboost
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