Research Article
Recognition of Imbalanced Epileptic EEG Signals by a Graph-Based Extreme Learning Machine
Table 8
Results of all methods on the AUC index.
| Datasets | ELM | W1-ELM | W2-ELM | R1-ELM | R2-ELM | G-ELM |
| D1 | 0.8542(0.0035) | 0.8371(0.0088) | 0.8679(0.0167) | 0.9175(0.0009) | 0.9125(0.0034) | 0.9458(0.0012) | D2 | 0.8367(0.0042) | 0.8418(0.0159) | 0.8438(0.0117) | 0.9117(0.0016) | 0.9067(0.0023) | 0.9408(0.0015) | D3 | 0.8750(0.0055) | 0.8409(0.0102) | 0.8319(0.0120) | 0.9108(0.0025) | 0.9050(0.0022) | 0.9517(0.0015) | D4 | 0.8442(0.0042) | 0.8162(0.0113) | 0.8546(0.0176) | 0.9067(0.0011) | 0.8950(0.0024) | 0.9375(0.0016) | D5 | 0.7372(0.0054) | 0.8296(0.0070) | 0.8239(0.0128) | 0.8607(0.0020) | 0.7939(0.0035) | 0.9089(0.0025) | D6 | 0.7839(0.0071) | 0.8616(0.0156) | 0.8403(0.0147) | 0.8922(0.0027) | 0.8339(0.0072) | 0.9217(0.0004) | D7 | 0.8322(0.0041) | 0.8569(0.0166) | 0.8165(0.0067) | 0.9056(0.0016) | 0.9072(0.0022) | 0.9344(0.0009) | D8 | 0.8583(0.0037) | 0.8319(0.0167) | 0.8561(0.0114) | 0.9128(0.0025) | 0.9094(0.0023) | 0.9444(0.0007) | D9 | 0.8275(0.0062) | 0.8494(0.0119) | 0.7990(0.0070) | 0.8938(0.0026) | 0.8794(0.0020) | 0.9263(0.0010) | Ave | 0.8277 | 0.8406 | 0.8371 | 0.9013 | 0.8826 | 0.9346 | Ave. std | 0.0049 | 0.0127 | 0.0123 | 0.0019 | 0.0031 | 0.0013 |
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