In the k nearest neighbor technique, a small value of k produces classifications that are
A) very sensitive to the sample-specific characteristics of the training data
B) not sensitive to the sample-specific characteristics of the training data
C) robust
D) reliable

Question

Quizplus · Accepted Answer

A small value of k in k-nearest neighbor technique means that the classification is based on a small number of nearest neighbors, which can be sensitive to the sample-specific characteristics of the training data. As a result, the classification may not be reliable and might overfit to the training data. Therefore, a larger value of k is generally preferred to achieve more robust and reliable classifications.

In the K Nearest Neighbor Technique, a Small Value of K