10-601 Evaluation
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Revision as of 13:41, 24 September 2013 by Wcohen (talk | contribs) (→What You Should Know Afterward)
This a lecture used in the Syllabus for Machine Learning 10-601
Slides
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.
