10-601 Ensembles 2

This a lecture used in the Syllabus for Machine Learning 10-601 in Fall 2014

Slides

• Slides in PowerPoint.
• Margin "movie" I showed in class: Margin movie.

• I also did a demo of Weka. There's a presentation on the weka GUIs which covers some of the same material.

Readings

• Ensemble Methods in Machine Learning, Tom Dietterich
• A Short Introduction to Boosting, Yoav Freund and Robert Schapire.
• Optional: Improved boosting algorithms using confidence-rated predictions, Robert Schapire and Yoram Singer. (This paper has the analysis that I presented in class.)

Summary

You should understand the basic intuitions behind the analysis of boosting:

• As reducing an upper bound on error and hence fitting the training data.
• As a coordinate descent optimization of the same upper bound.

You should also be aware that boosting is related to margin classifiers.