How do you handle noisy data in KNN systems?

Noise is handled using weighting, smoothing, filtering, or robust distance metrics.

Noisy data introduces misleading neighbors. Weighted KNN reduces impact of distant noisy points. Preprocessing techniques like outlier removal or smoothing improve stability.