6.1. C(HighRisk or LowRisk), using lagged ranges as x-variables. How well does NB do compared to knn using the kcvSearch to select k from the train data? To make this a fair comparison, you need to run knn on the same train-test split that you gave to the NB program.
6.2 Add 8 more lags to your stock range data - the Hi-risk vs Lo-risk data. Do that in Excel using our best practices method. Try running kNN and klaR with that data and with the same train-test split.
(a) What changes do you observe in the performance?
(b) Did adding more regressors (more lags) effect the choice of k in kNN?
(c) Did that slow down the kcvSearch program? Why would that matter?
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