Difference between revisions of "10-601 Naive Bayes"
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| − | == Assignment == | + | === Assignment === |
* Implement Naive Bayes and apply it to a couple of datasets. (Details to be posted later.) | * Implement Naive Bayes and apply it to a couple of datasets. (Details to be posted later.) | ||
Revision as of 10:16, 3 July 2013
This a lecture used in the Syllabus for Machine Learning 10-601
Slides
- Slides in Powerpoint. Based on the slides I used for 10-605, they might be updated.
Readings
- None
Assignment
- Implement Naive Bayes and apply it to a couple of datasets. (Details to be posted later.)
What You Should Know Afterward
- How to implement the multinomial Naive Bayes algorithm
- How to interpret the predictions made by the algorithm
