Difference between revisions of "10-601 Ensembles 1"
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| + | This a lecture used in the [[Syllabus for Machine Learning 10-601]] | ||
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=== Slides === | === Slides === | ||
Revision as of 10:44, 31 October 2013
This a lecture used in the Syllabus for Machine Learning 10-601
Slides
Readings
- Ensemble Methods in Machine Learning, Tom Dietterich
- A Short Introduction to Boosting, Yoav Freund and Robert Schapire.
Summary
You should know how to implement these ensemble methods, and what their relative advantages and disadvantages are:
- Bagging
- Boosting
- Stacking
- Multilevel Stacking
- The "bucket of models" classifier
