Difference between revisions of "10-601 Perceptrons and Voted Perceptrons"
From Cohen Courses
Jump to navigationJump to search (→Slides) |
|||
| (One intermediate revision by the same user not shown) | |||
| Line 1: | Line 1: | ||
| − | This a lecture used in the [[Syllabus for Machine Learning 10- | + | This a lecture used in the [[Syllabus for Machine Learning 10-601B in Spring 2016]] |
=== Slides === | === Slides === | ||
| − | * [http://www.cs.cmu.edu/~wcohen/10-601/voted-perceptron.pptx Slides in Powerpoint] | + | * [http://www.cs.cmu.edu/~wcohen/10-601/voted-perceptron.pptx Slides in Powerpoint] |
=== Readings === | === Readings === | ||
Latest revision as of 15:17, 6 January 2016
This a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016
Slides
Readings
- My notes on the voted perceptron. (You can skip sections 3-4 on ranking and the structured perceptron).
- Optional reading: Freund, Yoav, and Robert E. Schapire. "Large margin classification using the perceptron algorithm." Machine learning 37.3 (1999): 277-296.
- Optional background on linear algebra: Zico Kolter's linear algebra review lectures
What You Should Know Afterward
- The difference between an on-line and batch algorithm.
- How to implement the voted perceptron.
- The definition of a mistake bound, and a margin.
