Advantages vs Disadvantages of K-Nearest Neighbors

Advantages: • White box model • No training needed (only parameter tuning) • Non linearity • Only one parameter to tune (K) Disadvantages: • Can be slow with large datasets • Scaling is necessary for the distance measure to work properly • Sensible to outliers • Curse of dimensionality