Table 1 Classification performance of the algorithm versus the ground truth events for Driving Data 1 for three data conditions: the full data without partitioning, the training data and the testing data, respectively
From: Detecting alpha spindle events in EEG time series using adaptive autoregressive models
| Full data | Training data | Testing data | |
|---|---|---|---|
| Sensitivity/Recall | .915 | .895 | .863 |
| Specificity | .966 | .966 | .984 |
| Precision | .536 | .612 | .581 |
| Hit Rate | 97.87% (138/141) | 100% (96/96) | 93.33% (42/45) |
| Spindle Temporal Error | ~96 ms | ~120 ms | ~150 ms |
| Agreement | 146.430 s | 98.617 s | 43.055 s |
| Null Agreement | 3591.156 s | 1762.414 s | 1861.141 s |
| False Negative | 13.586 s | 11.531 s | 6.813 s |
| False Positive | 126.828 s | 62.445 s | 31.000 s |