Question: For KNN classification, why do we divide our data into a training and test set? Should we use our test set to find the best

For KNN classification, why do we divide our data into a training and test set? Should we use our test set to find the best possible number of neighbors for a k-NN classifier? What is the point of a test set, and why do we only want to use the test set once? Explain.

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