Question
Why can choosing k = 1 make a k-NN classifier sensitive to noise?
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Correct Answer: D. Each prediction depends entirely on the single closest training point
Explanation:
One mislabeled or unusual training case can determine the prediction in its neighborhood. This low-bias, high-variance setting can overfit the training data.
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