Question

In k-nn algorithm, given a set of training examples and the value of k < size of training set (), the algorithm predicts the class of a test example to be the

Answer 1

The algorithm predicts the class of a test example to be the most frequent class among the classes of k closest training examples.

Answer 2

KNN has no model other than storage of the entire dataset, so there is no learning required for it.

Efficient implementations can pile the data using complex data structures like k - d trees to make look up and equivalent of new patterns which is done during the prediction efficient.