Table 2 Running times (%d) of all methods on real datasets and high dimensional datasets.
From: A local adaptive fuzzy spectral clustering method for robust and practical clustering
Datasets | K-means | FCM | NC | CAN | FSC |
|---|---|---|---|---|---|
Australian | 0.0211 | 0.1859 | 5.0242 | 16.2813 | 17.6541 |
Breast | 0.0000 | 0.1055 | 4.5734 | 4.2344 | 4.3569 |
Cleve | 0.0039 | 0.1414 | 0.9477 | 3.3906 | 3.4789 |
Diabetes | 0.0492 | 0.1383 | 5.8063 | 6.4375 | 7.5693 |
Glass | 0.0352 | 0.1984 | 0.5070 | 0.6719 | 0.7189 |
Heart | 0.0219 | 0.1664 | 0.7102 | 0.7656 | 0.7482 |
Iris | 0.0391 | 0.0227 | 0.3609 | 0.3906 | 0.4021 |
Segment | 0.0859 | 3.2156 | 86.1211 | 74.4219 | 80.3645 |
Waveform | 0.0836 | 0.9563 | 127.9625 | 322.2656 | 342.1456 |
Wine | 0.0219 | 0.0914 | 0.3203 | 0.5781 | 0.5612 |
Coil | 1.0516 | 7.7250 | 37.1773 | 52.0469 | 57.2564 |
Mnist | 3.8289 | 3.9500 | 245.2844 | 585.0025 | 612.3125 |
MSRA | 0.6609 | 4.9875 | 50.8930 | 53.1250 | 55.0244 |
Palm | 0.8250 | 5.5250 | 48.1820 | 59.5156 | 65.3212 |
USPS | 0.7883 | 2.1688 | 39.5844 | 97.9531 | 107.2530 |
