Table 2

Classification performance of the algorithm versus the ground truth events for Driving Data 1 and Driving Data 2 for three data conditions: the full data without partitioning, the training data and the testing data, respectively
Full data Training data Testing data
Data 1 Data 2 Data 1 Data 2 Data 1 Data 2
Sensitivity/Recall .957 .876 .959 .914 .952 .904
Specificity .981 .964 .974 .958 .989 .934
Precision .704 .620 .706 .660 .701 .400
Hit Rate 97.16% (137/141) 94.36% (184/195) 100% (96/96) 95.38% (124/130) 91.11% (41/45) 93.85% (61/65)
Spindle Temporal Error ~52 ms ~114 ms ~50 ms ~77 ms ~40 ms ~96 ms
Agreement 165.422 s 157.008 s 114.539 s 106.688 s 50.833 s 59.047 s
Null Agreement 3635.516 s 2584.453 s 1167.875 s 1257.414 s 1866.859 s 1275.273 s
False Negative 7.438 s 22.195 s 4.875 s 9.984 s 2.563 s 6.273 s
False Positive 69.625 s 96.344 s 47.720 s 54.922 s 21.703 s 89.414 s

A fuzzy window parameter of 0.1 s was used.

Lawhern et al.

Lawhern et al. BMC Neuroscience 2013 14:101   doi:10.1186/1471-2202-14-101

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