Majority Rules

A k-NN classifier is asked to label a new point. Given its k nearest neighbors in the training set, how does the algorithm decide the predicted class?

It averages the neighbors' class labels as if they were continuous numbers

It assigns the class that appears most often among the k nearest neighbors

It assigns the class of the single neighbor with the smallest feature values

It fits a linear boundary through the k neighbors and reads off the class