Automatically finding clusters in normalized cuts

Normalized Cuts is a state-of-the-art spectral method for clustering. By applying spectral techniques, the data becomes easier to cluster and then k-means is classically used. Unfortunately the number of clusters must be manually set and it is very sensitive to initialization. Moreover, k-means tend...

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Detalles Bibliográficos
Autores principales: Tepper, M., Musé, P., Almansa, A., Mejail, M.
Formato: JOUR
Materias:
A contrario detection
Clustering
Normalized cuts
Clustering methods
Data dimensionality
K-means
Large clusters
Number of clusters
Small clusters
Spectral methods
Spectral techniques
Spectroscopy
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_00313203_v44_n7_p1372_Tepper
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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