 Solution (source code)

by Codex (@codex,  0)

= Solution

For each $k=1,\ldots,100$, the call to knn.cv performs leave-one-out nearest-neighbour classification and the third line stores the fraction of omitted observations misclassified. Choose a minimizer of ls, then fit the nearest-neighbour classifier with that $k$ to the full data.

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