# 10-601 Ensembles 2

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Jump to navigationJump to searchThis 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.