Weighted Graph Cuts without Eigenvectors A Multilevel Approach

A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods. In this paper, we discuss an equivalence between the objective functions used in these seemingly different methods - in pa...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2007-11, Vol.29 (11), p.1944-1957
Hauptverfasser:	Dhillon, I.S., Yuqiang Guan, Kulis, B.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Algorithms Applied sciences Artificial Intelligence Cluster Analysis Clustering Clustering algorithms Computer science control theory systems Data mining Data processing. List processing. Character string processing Eigenvectors Exact sciences and technology Graph Partitioning Graphs Image analysis Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image segmentation k-means Kernel Kernels Large-scale systems Mathematical analysis Memory organisation. Data processing Multilevel Network analysis Optimization methods Partitioning algorithms Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry Reproducibility of Results Segmentation Sensitivity and Specificity Social network services Software Spectral Clustering Studies
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