# $k$ Nearest Neighbors > [!summary] $k$ NN Find the $k$ training instances that are the closest to the > test instance, and classify the test instance as the majority class of the $k$ > nearest training instances. - Choosing $k$ - Too small: overfitting, susceptible to noise - Too big: misclassify, instances far away are included - Majority voting vs. distance-weighted, or taking average.