### Regression in KNN Algorithm

K-Nearest Neighbor algorithm uses ‘feature similarity’ to predict values of any new data points. This means that the new point is assigned a value based on how closely it resembles the points in the training set. During regression implementation, the average of the values is taken to be the final prediction, whereas during the classification implementation mode of the values is taken to be the final prediction.