DSCI
724
Final Exam
Study Guide
Weeks 12-13
ISLR Chapter 9
1. What is the definition of the margin in a maximal margin linear classifier? p. 341
2. What is the definition of a support vector? pp. 341-2
3. How do maximal margin classifiers and support vector classifiers differ. p. 343
4. What are the characteristics of a classifier that constructs a separating hyperplane that perfectly
classifies the training observations? p. 344
5. What characteristic defines how the support vector classifier margin becomes soft. p. 345
6. When does the support vector classifier perform poorly? p. 349
7. What technique is used by support vector machines to separate classes with a non-linear decision
boundary? p. 349-50
8. What makes the computation of the solution to the support vector classifier easier? p. 351
9. How is a kernel defined in a support vector machine context? p. 352
10. What components are used to build a support vector machine? p. 352
11. What differentiates a radial kernel from a polynomial kernel? p. 352-3
12. Review the figures in chapter 9 and ensure that you understand them.