874: Pattern Recognition

 

Handouts:

 

1.      Introduction

2.      Feature Space and Feature Extraction

3.      Bayes and the Normal Model

4.      Linear Discriminant Functions

5.      Mixture and Markov Models

6.      Nonparametric Techniques

7.      Algorithm-independent Learning

8.      Comparing Classifiers

 

 

Readings:

 

 

 

Homework:

 

        Homework 1: description.

Due date: Thurs, April 12 @ noon.

 

        Homework 2: description.

Due date: Thurs, April 19 @ noon.

 

        Homework 3: Mixture of Gaussians (data).

Due date: Thurs, May 10 @ noon

 

Projects:

 

        Project 1: Study of the Bayes classifier with Normal densities.

See handouts for details.

Due: Tues, April 24 @ noon.

 

        Final Project: Description, databases.

Due: Thurs, May 31.

 

Syllabus:

 

        Spring 2007.