Difference between revisions of "10-601 Naive Bayes"
From Cohen Courses
Jump to navigationJump to searchLine 2: | Line 2: | ||
=== 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], [http://www.cs.cmu.edu/~wcohen/10-601/nb.pdf Slides in PDF] |
=== Readings === | === Readings === |
Revision as of 10:01, 20 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, Slides in PDF
Readings
- Mitchell 6.1-6.10
- Murphy 3
- 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