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Computer Science 8751

Advanced Machine Learning

Homework Assignment 3 (20 points)

Due March 23, 2009

- A machine learning problem has four input features:
*A*, which has possible values *A1*, *A2* and *A3*; *B*, which has possible values of *yes* and *no*, *C* which can take on any value from *0.0* to *150.0*, and *D* which has possible values of *true*, *false* or *unknown*. The output class to be calculated has four possible values: *tiny*, *small*, *medium* or *large*. What input and output representation would you use for this problem when applying *k*-nearest neighbors and explain the advantages and disadvantages of your representations.
- How would you represent hypotheses for a genetic algorithm with one or more rules for the above problem. Make sure to precisely define your bit strings, your crossover and mutation operators.
- Exercise 10.2, page 303