Research Article
NMFBFS: A NMF-Based Feature Selection Method in Identifying Pivotal Clinical Symptoms of Hepatocellular Carcinoma
Table 7
Classification accuracy of inferred optimal feature subset via NMFBFS, ReliefF, mRMR, and Elastic Net on the training set.
| Methods | Feature subset | Dimension | Classification accuracy in LSSVM (%) |
| NMFBFS | | 39 | 80.002 ± 9.95 |
| ReliefF | FSRF20 | 20 | 65.00 ± 10.03 | FSRF40 | 40 | 73.33 ± 15.76 |
| mRMR | FSMR20 | 20 | 70.83 ± 12.5 | FSMR40 | 40 | 74.17 ± 9.03 |
| Elastic Net | FSEN20 | 20 | 70.00 ± 11.56 | FSEN40 | 40 | 76.67 ± 10.46 |
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