What is a major drawback to the basic majority voting classification in kNN?
A) It requires frequent human subjective input during computation.
B) Classes that are more clustered tend to dominate prediction.
C) Even the naive version of the algorithm is hard to implement.
D) Classes with more frequent examples tend to dominate prediction.

Question

Quizplus · Accepted Answer

The major drawback of the basic majority voting classification in kNN is that classes with more frequent examples tend to dominate prediction. This is because the algorithm simply assigns a label based on the most common class among the k nearest neighbors. Therefore, classes that have more examples in the dataset will have a greater chance of being selected as the prediction.

What Is a Major Drawback to the Basic Majority Voting