Table 2. Performance of Classifiers for DLMO Estimation in College Students.
The classification accuracy of whether a timepoint falls before or after experimentally observed DLMO in cross-validation (mean ± standard deviation) and on the independent test set on different subsets of the data.
| Cross-Validation Results | |||||
| Model | Full Dataset | Actigraphy Data | Activity & Skin Temperature | Activity & Light | Light & Skin Temperature |
| Single Layer | 89.1±3.7 (100 nodes) |
89.4±3.6 (90 nodes) |
88.8±3.4 (50 nodes) |
89.8±3.4 (90 nodes) |
87.0±3.0 (30 nodes) |
| Single Layer with Dropout | 89.3±3.4 (p=0.4) |
89.3±3.2 (p=0.3) |
89.1±2.9 (p=0.5) |
89.5±3.8 (p=0.5) |
87.1±3.4 (p=0.2) |
| Double Layer | 88.9±3.6 (50x50 nodes) |
89.3±3.6 (30x50 nodes) |
89.2±3.5 (30x40 nodes) |
90.0±3.9 (40x40 nodes) |
86.8±3.7 (30x40 nodes) |
| Double Layer with Dropout | 89.3±3.3 (p=0.4) |
89.5±3.4 (p=0.3) |
88.7±3.2 (p=0.1) |
89.6±3.8 (p=0.4) |
87.1±2.9 (p=0.2) |
| Test Results | |||||
| Model | Full Dataset | Actigraphy Data | Activity & Skin Temperature | Activity & Light | Light & Skin Temperature |
| Single Layer | 90.7 | 90.2 | 89.1 | 89.9 | 86.1 |
| Single Layer with Dropout | 89.9 | 90.2 | 89.8 | 89.8 | 85.8 |
| Double Layer | 90.1 | 90.9 | 89.4 | 90.5 | 86.4 |
| Double Layer with Dropout | 89.2 | 89.8 | 88.8 | 90.1 | 85.1 |