Table 6 1D-CNN Model Validation Metrics on FULL-256 data set for each fold.

From: Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection

Fold

ACC

Loss

F1

Precision

Recall

1

0.8758

0.3077

0.8745

0.8782

0.8708

2

0.7917

0.5703

0.8227

0.7160

0.9667

3

0.8375

0.4113

0.8169

0.9355

0.7250

4

0.6042

1.6410

0.6494

0.5828

0.7333

5

0.7625

0.5687

0.8034

0.6853

0.9708

6

0.7375

0.5966

0.6519

0.9672

0.4917

Avg.

0.7682

0.6826

0.7698

0.7942

0.7931

Std.

0.0947

0.4828

0.0954

0.1547

0.1827

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