Question: K-nearest neighbor method predicts the label for a given data point. by averaging k clos, points to that data point Will model complexity increase, as

  1. K-nearest neighbor method predicts the label for a given data point. by averaging k clos, points to that data point
  1. Will model complexity increase, as k increases? Why?
  2. Will bias error increase as In increases? Why?
  3. What is a good method to select a value for k?

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