Research Article
An Efficient Approach to Solve the Large-Scale Semidefinite Programming Problems
Table 1
UCI datasets used together with some characteristics and the clustering results achieved using the different methods.
| Dataset | | Size | Dims. | Accuracy | K-means | Spectral clustering | SDP relaxation | Ours | CVX |
| Soybean | 4 | 47 | 36 | 0.723 | 0.745 | 0.766 | 0.766 | Iris | 3 | 150 | 5 | 0.893 | 0.933 | 0.947 | 0.953 | Wine | 3 | 178 | 13 | 0.702 | 0.725 | 0.730 | 0.730 | SPECTF heart | 2 | 267 | 44 | 0.625 | 0.802 | 0.816 | 0.816 |
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