In this exercise, you will investigate the use of a k$-$NN classifier on the Stock Market data used in the lab

lesson, and in particular you will investigate the bias$/$variance trade$-$off behind the choice of k$.$

$$ Split the Stock Market data into a train and test partition, using the same criterion adopted in the lab

lesson $($temporal split$).$

$$ Using Lag$1$ and Lag$2$ as predictors, fit a k$-$NN classifier with different values of k $($for example, from $1$

to $100).$

$$ Evaluate the train and test errors of each model and plot them as a function of $1/$k$.$