This is an intuitive implementation of Spectral Clustering with MATLAB. You can easily finish a spectral clustering analysis using Scikit-Learn similar API (the comparison between spectral clutsering and others is here). For more deatils about spectiral clustering, you can read the references below or a brief introduction written by us. (GPU accelerated version will be coming soon...)
- Clone this repo and run
main.mto see the demo - Usage Details
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Specify your data matrix X and label vector y, or get the built-in data
[X, y] = make_digits_dataset(300, true, false); % 300 examples, balance, no shuffleIn this project, we provide 6 datasets including 3 toys and 3 real datasets. You can find them in
datasets. -
Construct your graph
W = fullyconnected(X, 7.8, 'rbf');There havs 3 types of graph you can use. Find them in
graph. -
Run the Spectral Clustering Solver
[C, ~] = SpectralClustering(W, size(unique(y), 1), 2);C is the predicted clusters.
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You can also easily metric the predicted answer with the functions under the
metric.
- Liu Jun-Hao, SCUT
- Ning Jin-Lai, SCUT
- Huang De-Dong, SCUT
- Wen Hao, SCUT
- Von Luxburg, Ulrike. "A tutorial on spectral clustering." Statistics and computing 17.4 (2007): 395-416.