Code covered by the BSD License
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GenData_Ellipse( num, r, var,...
GENDATA_ELLIPSE Calculates a ellipse sample data set
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GenData_Gaussian( num, mu, si...
GENDATA_GAUSSIAN Calculates a Gaussian sample data set
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SimGraph( M, Type, Param, var...
SIMGRAPH Returns adjacency matrix for M
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SpectralClustering( W, k, Typ...
SPECTRALCLUSTERING Executes spectral clustering algorithm
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distEuclidean( M, N )
DISTEUCLIDEAN Calculates Euclidean distances
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plotSimGraph( T, W, Colored, ...
PLOTSIMGRAPH Plots similarity graph
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simGaussian( M, sigma )
SIMGAUSSIAN Calculates Gaussian similarity on matrix
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simInverse( M )
SIMINVERSE Calculates similarity as inverse distances
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Demo.m
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View all files
Fast and efficient spectral clustering
by Ingo
02 Jan 2012
(Updated 24 Apr 2012)
Perform fast and efficient spectral clustering algorithms
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Watch this File
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| File Information |
| Description |
SpectralClustering performs one of three spectral clustering algorithms (Unnormalized, Shi & Malik, Jordan & Weiss) on a given adjacency matrix. SimGraph creates such a matrix out of a given set of data and a given distance function.
The code has been optimized (within Matlab) to be both fast and memory efficient. Please look into the files and the Readme.txt for further information.
References:
- Ulrike von Luxburg, "A Tutorial on Spectral Clustering", Statistics and Computing 17 (4), 2007
If there are any questions or suggestions, I will gladly help out. Just contact me at admin (at) airblader (dot) de |
| Required Products |
Statistics Toolbox
MATLAB
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| MATLAB release |
MATLAB 7.13 (2011b)
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| Updates |
| 03 Jan 2012 |
- Updated some files
- Included Demo |
| 04 Jan 2012 |
Minor updates |
| 08 Jan 2012 |
Got rid of redundant code |
| 08 Jan 2012 |
fixed wrong code in demo file |
| 13 Jan 2012 |
Fixed critical bug when creating sparse matrices
Demo now plots similarity graph (only use for few data points!)
Minor changes |
| 19 Jan 2012 |
- Fixed critical mistake when creating similarity graphs
- Restructured some of the code |
| 24 Apr 2012 |
Included acknowledgements |
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Contact us at files@mathworks.com
