Research Article
One-Class Classification with Extreme Learning Machine
Table 4
The value of precision and recall for two datasets (arrhythmia and E. coli).
| Dataset | Arrhythmia | E. coli | Classifier | Precision | Recall | Precision | Recall |
| Naive Parzen | 45.6 | 96.0 | 63.7 | 86.2 | Parzen | 52.0 | 82.4 | 71.5 | 80.6 | -means | 52.5 | 81.0 | 52.4 | 64.6 | 1-NN | 44.5 | 88.6 | 12.1 | 90.2 | -NN | 47.8 | 90.2 | 31.9 | 87.3 | Autoencoder | 52.6 | 84.7 | 47.3 | 73.5 | PCA | 79.1 | 15.9 | 23.2 | 74.4 | MST | 47.3 | 91.8 | 23.9 | 90.0 | -centers | 50.4 | 83.4 | 29.3 | 68.9 | SVDD | 55.7 | 69.3 | 48.8 | 66.9 | MPM | 64.0 | 43.9 | 38.4 | 45.4 | LPDD | 51.7 | 83.3 | 67.8 | 75.4 | SVM | 52.4 | 80.5 | 57.8 | 65.8 | ELM | 52.8 | 80.1 | 83.2 | 72.3 |
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