Department of Computer Science Pattern Recognition (Topics in Artificial Intelligence, Winter 2009-2010) 4005-759-01 (Calendar Description)

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Instructor: Richard Zanibbi, Office: 70-3551 (Golisano College)
Office hours: 2-3pm Tues. and Thurs., 10am-12pm on Wednesdays
Lectures: 4-5:50pm Tuesdays and Thursdays, Room 70-3445 (Golisano College)

PRTools Examples

Tutorial/Examples: There is a set of exercises giving example uses of PRTools available online here. A number of datasets needed for the examples (and for your own experimentation) are available here.

The PRTools MATLAB toolkit we will be using in-class and for the project for may be downloaded from prtools.org: you will want to download the academic version. Make sure to add it to your MATLAB path (from the File menu, click: File -- Set Path). For those new to MATLAB, there are a number of tutorials online, and MATLAB comes with a large set of demonstrations (look under the 'Help' menu).

The PRTools distribution comes with a nice overview and reference manual given as a .pdf in the prtools_ac directory. The overview, summary of built-in examples and reference tables in Section 7 are particularly useful.

Week 1

• Clustering Banana-shaped data sets using k-means clustering: clustereg.m
• Generating samples of Gaussian (normal) distributions and plotting them in MATLAB: gdisteg.m

Week 2

• Creating, displaying, and testing a linear discriminant classifier (LDC: classes assumed to be normally distributed with identical covariance matrices): lineareg.m
• Using the Quadratic Discriminant Classifier (QDC: Classes assumed to be normally distributed, but with different covariance matrices): quadeg.m
• A similar example, but using k-Nearest Neighbor classification: nn.m

Week 3

• Voronoi diagrams (illustrating decision regions for 1-NN, points in the plane closest to each training sample):
  • voronoieg.m
  • voronoieg2.m