This problem involves the

OJ

data set in the

ISLR

package.

a$)$

Create a training set containing a random sample of $900$ observations and a test set containg the

remaining observations.

b$)$

Fit a support vector classifier to the training set using

cost $=0\mathrm{.}01$

with

Purchase

as the response

and the other variables as predictors. Use the

summary$()$

function to produce summary statistics

and describe the results obtained.

c$)$ What are the training and test error rates?

d$)$ Use CV to select an optimal

cost

$.$ Consider values between

$0$

$.$

$01$

and

$10$

$.$

e$)$ Compute the training and test error rates using this new value for

cost

$.$

f$)$

Repeat b$)$ through e$)$ using a support vector machine with a radial kernal and default value for

gamma

$.$

g$)$ Repeat b$)$ through e$)$ using a support vector machine with a polynomial kernal and

degree $=2$

$.$

h$)$ Which approach gives the best results on this data?

$4$