Spectral Clustering Explained: Why Eigenvectors Beat K-Means
Spectral clustering outperforms K-means for non-linear data structures by leveraging graph theory and eigenvectors. This guide explains how to build a Laplacian matrix from scratch, use the eigengap heuristic to determine clusters, and optimize the gamma hyperparameter for robust machine learning results in Python and Scikit-learn.