10-601 Naive Bayes

From Cohen Courses

Revision as of 10:03, 20 January 2016 by Wcohen (talk | contribs) (→‎Slides and Other Materials)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

Jump to navigation Jump to search

This a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016

Slides and Other Materials

Catchup - MAP and Joint Distribution: Slides in Powerpoint, Slides in PDF
Main 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

Retrieved from "http://curtis.ml.cmu.edu/w/courses/index.php?title=10-601_Naive_Bayes&oldid=18280"

Navigation menu