Research Article
A Hybrid Method Based on Extreme Learning Machine and Self Organizing Map for Pattern Classification
Table 2
Results of Experiments on classification problem.
| Datasets | Algorithms | Training time (s) | Testing accuracy | Hidden nodes |
| Ionosphere | BP | 33.944864 | 82.8571 | 20 | ELM | 0.667364 | 87.6190 | 40 | TROP-ELM | 0.6517 | 89.2900 | 51 | Proposed | 0.396109 | 92.3810 | 31 |
| Iris | BP | 29.232330 | 93.3333 | 15 | ELM | 0.235005 | 95.5556 | 40 | TROP-ELM | 0.0738 | 96.6700 | 59 | Proposed | 0.052971 | 100 | 15 |
| Wine | BP | 31.336370 | 94.2308 | 18 | ELM | 0.218872 | 96.1538 | 35 | TROP-ELM | 0.1242 | 96.5800 | 84 | Proposed | 0.092291 | 100 | 22 |
| Balance | BP | 136.802525 | 76.1905 | 10 | ELM | 1.121717 | 83.0688 | 28 | TROP-ELM | 0.3224 | 87.2100 | 56 | Proposed | 0.474296 | 87.5661 | 13 |
| Zoo | BP | 34.132912 | 80.6452 | 10 | ELM | 0.082092 | 93.5484 | 15 | TROP-ELM | 0.0316 | 94.5000 | 18 | Proposed | 0.030456 | 97.2350 | 7 |
| Image segmentation | BP | 428.141558 | 87.8582 | 15 | ELM | 24.629949 | 91.3008 | 90 | TROP-ELM | 207.8026 | 90.4300 | 187 | Proposed | 11.964243 | 96.4131 | 70 |
| Ecoli | BP | 55.678908 | 71.4286 | 15 | ELM | 0.646599 | 85.9890 | 40 | TROP-ELM | 0.5869 | 92.0700 | 90 | Proposed | 0.252657 | 93.6813 | 26 |
| Multiple features | BP | 226.625993 | 90.9000 | 12 | ELM | 67.085971 | 97.6833 | 180 | TROP-ELM | 190.431 | 98.4300 | 338 | Proposed | 40.753813 | 99.0333 | 121 |
| Jaffe | BP | 427.894980 | 75.4464 | 20 | ELM | 1.778349 | 81.9196 | 130 | TROP-ELM | 1.668231 | 83.4550 | 240 | Proposed | 1.530555 | 84.3750 | 99 |
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