Spectral Clustering

A clustering method that aims to discover complex cluster structures using similarity graphs and eigen decomposition.

Spectral clustering forms clusters by analyzing similarity relationships among data points through a graph structure. It can be especially advantageous in nonlinear or complex-shaped cluster settings where centroid-based methods struggle. While mathematically elegant, it requires careful use because of similarity-matrix construction cost and sensitivity to parameter choices. It encourages thinking about clustering in relational rather than purely geometric terms.