Spectral clustering is a powerful unsupervised machine learning algorithm for data with non convex or nested structures. With roots in graph theory, it uses the spectral properties of Laplacian matrix to project low-dimensional space where more efficient. Despite its success tasks, suffers practice from fast-growing running time $O(n^3)$, $n$ number points dataset. In this work we propose an en...
