How does PCA interact with clustering algorithms?

PCA improves clustering by reducing noise and dimensionality before applying clustering algorithms.

High-dimensional data suffers from distance concentration. PCA reduces dimensionality, improving clustering quality for algorithms like K-Means by enhancing meaningful distance separation.