Research Article
A Novel Ensemble Credit Scoring Model Based on Extreme Learning Machine and Generalized Fuzzy Soft Sets
Table 6
Running time for all models with feature selection (seconds).
| Data sets | Models | C5.0 | SVM-R | DBN | Bayes | ELM |
| Germany | 1.76 | 2.89 | 4.33 | 1.72 | 1.38 | Australia | 1.16 | 2.02 | 2.99 | 1.07 | 0.97 | Japan | 1.25 | 2.05 | 2.90 | 1.13 | 0.94 | Iran | 1.82 | 3.01 | 4.31 | 1.69 | 1.44 | Bene 1 | 5.63 | 10.11 | 14.29 | 5.85 | 4.62 | Bene 2 | 12.71 | 21.13 | 28.96 | 12.32 | 10.01 | Shuttle | 21.79 | 35.78 | 53.61 | 21.29 | 17.11 | Skin_segment | 207.20 | 340.24 | 509.76 | 202.49 | 182.46 | MiniBooNE | 354.38 | 581.92 | 871.87 | 346.33 | 277.87 | LC2017Q1 | 591.26 | 970.78 | 1254.49 | 560.57 | 436.04 |
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