Research Article
Detecting Depression Using an Ensemble Logistic Regression Model Based on Multiple Speech Features
Table 7
Classification outcomes of ELRDD-E.
| Gender | Classifier | Sensitivity (%) | Specificity (%) | Accuracy (%) |
| Male | ELRDD-E | 78.13 | 85.29 | 81.82 | Adaboost decision tree | 65.63 | 82.35 | 74.24 | Bagging decision tree | 65.63 | 79.41 | 72.73 | Random forest | 62.50 | 79.41 | 71.21 | STEDD | 75.00 | 85.29 | 80.30 | Female | ELRDD-E | 79.25 | 70.59 | 75.00 | Adaboost decision tree | 64.15 | 76.47 | 70.19 | Bagging decision tree | 62.26 | 74.51 | 68.27 | Random forest | 66.04 | 76.47 | 71.15 | STEDD | 77.36 | 74.51 | 75.96 |
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