R$-$Studio Lab Homework:

Set seed to $1$ first by executing set.seed$(1)$ command.

Include relevant code for each problem. Include the output where necessary

$1.$ This question should be answered using the Weekly data set, which is part of the ISLR

package. This data is similar in nature to the Smarket data, except that it contains $1,089$

weekly returns for $21$ years, from the beginning of $1990$ to the end of $2010.$ Please

include necessary output with code for each problem.

a$.$ Fit Logistic regression model using a training data period from $1990$ to $2008$ with

Direction as response and the five lag variables plus Volume as predictors.

Include the confusion matrix below and calculate the accuracy and misclassification

rate for the test data $($that is$,$ the data from $2009$ and $2010).$

Include all relevant codes. Relevant codes are creation of training and test data to

fitting the model to obtaining the probabilities of success and creating the confusion

matrix.

b$.$ Fit LDA model using a training data period from $1990$ to $2008$ with Direction as

response and the five lag variables plus Volume as predictors.

Include the confusion matrix below and calculate the accuracy and misclassification

rate for the test data $($that is$,$ the data from $2009$ and $2010).$

Include all relevant codes.

c$.$ Repeat $($a$)$ using KNN$.$ First find optimal k using $10-$fold cross$-$validation. Then use

the optimal k to fit the knn model on the test data and then calculate the appropriate

confusion matrix. Include your confusion matrix below.

Include all relevant codes.

Which of the three methods $($Logistic$,$ LDA and KNN$)$ offer the better test accuracy

and least test error rate?