Difference between revisions of "10-601 Naive Bayes"
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=== Slides and Other Materials === | === Slides and Other Materials === | ||
| − | + | * William's lecture: [http://www.cs.cmu.edu/~wcohen/10-601/nb.pptx Slides in Powerpoint] | |
| − | * William's lecture: [http://www.cs.cmu.edu/~wcohen/10-601/nb.pptx Slides in Powerpoint | ||
* I did some examples in Matlab: | * I did some examples in Matlab: | ||
** [[jointDistCommands.m|A joint distribution for a die-rolling problem.]] | ** [[jointDistCommands.m|A joint distribution for a die-rolling problem.]] | ||
Revision as of 14:27, 6 January 2016
This a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016
Slides and Other Materials
- William's lecture: Slides in Powerpoint
- I did some examples in Matlab:
Readings
- Mitchell 6.1-6.10
- My favorite on-line Matlab docs
What You Should Know Afterward
- What conditional independence means
- How to implement the multinomial Naive Bayes algorithm
- How to interpret the predictions made by the NB algorithm
