MIT: Machine Learning 6.036, Lecture 12: Decision trees and random forests (Fall 2020)
* Lecture 12 for the MIT course 6.036: Introduction to Machine Learning (Fall 2020 Semester)
* Full lecture information and slides: http://tamarabroderick.com/ml.html
* Lecture date: 2020 / 11 / 17
* Lecturer: Tamara Broderick
* Lecture TAs: Crystal Wang and Satvat Jagwani
If you find any ways to improve how well the video captions reflect the live lectures, please submit a pull request to: https://github.com/tbroderick/ml_6036_2020_captions
0:00:00 Overview & Review
0:02:20 Predictive performance and beyond
0:08:38 Decision tree
0:13:50 Classification tree
0:15:42 Regression tree
0:24:46 Decision tree: a familiar pattern
0:30:51 Building a decision tree
0:59:59 How to regularize?
1:05:53 Ensembling
1:09:15 Bagging
1:15:30 Random forests
1:19:12 Decision trees & random forests: some pros and cons
Видео MIT: Machine Learning 6.036, Lecture 12: Decision trees and random forests (Fall 2020) канала Tamara Broderick
* Full lecture information and slides: http://tamarabroderick.com/ml.html
* Lecture date: 2020 / 11 / 17
* Lecturer: Tamara Broderick
* Lecture TAs: Crystal Wang and Satvat Jagwani
If you find any ways to improve how well the video captions reflect the live lectures, please submit a pull request to: https://github.com/tbroderick/ml_6036_2020_captions
0:00:00 Overview & Review
0:02:20 Predictive performance and beyond
0:08:38 Decision tree
0:13:50 Classification tree
0:15:42 Regression tree
0:24:46 Decision tree: a familiar pattern
0:30:51 Building a decision tree
0:59:59 How to regularize?
1:05:53 Ensembling
1:09:15 Bagging
1:15:30 Random forests
1:19:12 Decision trees & random forests: some pros and cons
Видео MIT: Machine Learning 6.036, Lecture 12: Decision trees and random forests (Fall 2020) канала Tamara Broderick
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