Title :
Spectral clustering for multiclass Erdös-Rényi graphs
Author :
Belabbas, Mohamed-Ali
Author_Institution :
Sch. of Eng. & Appl. Sci., Harvard Univ., Cambridge, MA, USA
Abstract :
In this article, we study the properties of the spectral analysis of multiclass Erdös-Rényi graphs. With a view towards using the embedding afforded by the decomposition of the graph Laplacian for subsequent processing, we analyze two basic geometric properties, namely interclass intersection and interclass distance. We will first study the dyadic two-class case in details and observe the existence of a phase transition for the interclass intersection. We then focus on the general multiclass case, where we introduce an appropriate notion of diagonal concentration and derive a statistical model that allows sampling graphs whose expected diagonal concentration is fixed. The simulations provided yield useful guidelines for practitioners to choose appropriately parameters in the context of spectral clustering.
Keywords :
graph theory; pattern clustering; spectral analysis; diagonal concentration; geometric property; graph Laplacian decomposition; interclass intersection; multiclass Erdos-Renyi graph; phase transition; sampling graph; spectral analysis; spectral clustering; Biological system modeling; Biology; Computational modeling; Context modeling; Graph theory; Guidelines; Laplace equations; Machine learning algorithms; Sampling methods; Spectral analysis; Community detection; Non-Euclidean datasets; Random graph models; Spectral graph theory;
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2010.5494932