What is the effect of using K-Nearest Neighbors (KNN) imputation on a dataset with high-dimensional feature space?

Question

Data Science — Hard

What is the effect of using K-Nearest Neighbors (KNN) imputation on a dataset with high-dimensional feature space?

Accepted Answer

In high-dimensional spaces, the distance between any two points tends to converge, a phenomenon known as the curse of dimensionality. Because KNN relies on distance metrics (like Euclidean distance) to find 'neighbors', these metrics become less meaningful as dimensions increase, causing the imputed values to be unreliable and noisy.