The K-NN Algorithm(2) N k-nn can be for continuous-valued labels Calculate the mean values of the k nearest neighbors w Distance-weighted nearest neighbor algorithm Weight the contribution of each of the k neighbors according to their distance to the query point x a Advantage X Robust to noisy data by averaging k-nearest neighbors 罐 Disadvantage Distance between neighbors could be dominated by irrelevant attributes 1010 The k-NN Algorithm (2) k-NN can be for continuous-valued labels. – Calculate the mean values of the k nearest neighbors Distance-weighted nearest neighbor algorithm – Weight the contribution of each of the k neighbors according to their distance to the query point xq Advantage: – Robust to noisy data by averaging k-nearest neighbors Disadvantage: – Distance between neighbors could be dominated by irrelevant attributes. w d x q x i  1 2 ( , )