# 10-601 Evaluation

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Jump to navigationJump to searchThis a lecture used in the Syllabus for Machine Learning 10-601 in Fall 2014

### Slides

- Ziv's lecture: Slides in pdf.
- William's lecture in Powerpoint, in PDF

### Readings

- Mitchell, Chapter 5.

### What You Should Know Afterward

- The difference between sample error and true error.
- What a confidence interval is.
- How to compute a confidence interval on the error rate of a classifier using the normal approximation.
- What a paired test is, and how to compute use a paired test to compare two classifiers.
- How to test the error rate of a classifier by cross-validation, or compare the error rates of two classifiers by cross-validation.