Computer Science 421
Advanced Artificial Intelligence
	
Department of Computer Science
University of Regina
Winter 2012

Assignment 5

Handout date:   March 30, 2012
Due Date:       April 11, 2012

1. (10 marks)
   Describe the main ideas of Naive Bayesian classification.

2. (10 marks)
   Describe an architecture of expert systems.

3. (10 marks)
   Give the Perceptron learning algorithm.  Explain why
   it is a good learning method.

4. (10 marks)
Consider the following set of examples, 
each with six inputs and one target output:

    I1  I2  I3  I4  I5  I6  Class
    _________________________________
    1   0   1   0   0   0     +
    1   0   1   1   0   0     +
    1   0   1   0   1   0     +
    1   1   0   0   1   1     +
    1   1   1   1   0   0     +
    1   0   0   0   1   1     +
    1   0   0   0   1   0     _
    0   1   1   1   0   1     +
    0   1   1   0   1   1     -
    0   0   0   1   1   0     -
    0   1   0   1   0   1     -
    0   0   0   1   0   1     -
    0   1   1   0   1   1     -
    0   1   1   1   0   0     -

Run the perception learning rule on these data and show the final weights.