CS539 MACHINE LEARNING. SPRING 99
Practice Problems for Exam 2
PROF. CAROLINA RUIZ
Department of Computer Science
Worcester Polytechnic Institute

Chapter 8
From Textbook: 8.3

Chapter 9
 From Textbook: 9.1, 9.3, 9.4
 Taken from Dean, Allen, and Aloimonos' book: Discuss how you would represent and
solve the traveling salesperson problem using genetic algorithms.
 Taken from Winston's book
 Suppose that you are testing various tent designs and tent materials
for comfort in winter. The temperature outside the tent is 40 degrees.
The temperature inside a tent of one designmaterial conmbination,
warmed by your body heat and a small stove is 5^{o}C. Ohter
tents produce temperatures of 10^{o}C and 15^{o}C.
 Compute the chances of survival of each combination using the
standard fitness method with inside temperature as the measure of quality
(the warmer the better).
 Now suppose that you have lost your Celsius thermometer, reducing
you to measuring temperature with a Fahrenheit thermometer. Recalculate
the chances of survival of each combination with the 41^{o}F,
50^{o}F, and 59^{o}F temperatures.
 Comment why your results argue against the use of the standard method.
 Suppose that you are using the rank method to select candidates.
Recall that the probability of picking the firstranked candidate is p.
If the first candidate is not pricked, then the probability of picking
the secondranked candidate is p (that is the second candidate's chance
of survival is p*(1p)), and so on, until only one candidate is left,
in which case it is selected.
 Suppose that you have five candidates. You decide to select
one using the rankspace method with p=0.25. Compute the probabilities
for each of the five as a function of rank.
 What is peculiar
about the probabilities that you computed in the previous part?
 Can you avoid the pecularity you observed in part 2 by restricting the
probability to a particular range?

Chapter 10
From Textbook: 10.1, 10.2, 10.3, 10.4, 10.5, 10.6, 10.7

Chapter 13
From Textbook: 13.1, 13.2, 13.3, 13.4