\# For this assignment, we are going to construct a KNN model to predict the stock market price \# movement. We are using Smarket dataset which is part of ISLR package. For more information about \# the variables in the data, please look up the help page for Smaket data (it is alwayse \# a good idea to inspect the dataset structure and explore the variables before running any * analytic model. \# 1. Prepare the variables of the model for the analysis (Normalize predictores). \# Remove the variable Today from the data \# 2. Set seed to 300 \# 3. Create an index for test and train instances ( 80/20split ) (observations) \# [direction is the Target feature] \# 4. Split the data into test and train \# 5. Build a KNN model with Direction as the target and all other variables as \# the predictors. Let the model try 30 different values for k. \# 6. plot the trained model. Approximately, at value of k the model has the highest Accuracy? \#7. Calculate the model performance measures (Accuracy, Sensitivity, and Specificity)