Table 9 1D-CNN-LSTM Model Validation Metrics for COGN-26 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

0.7688

0.5999

0.7861

0.7312

0.9758

2

0.7542

1.3300

0.8027

0.6704

1.0000

3

0.7250

1.2670

0.6207

1.0000

0.4500

4

0.7771

0.5214

0.8165

0.6939

0.9917

5

0.7271

0.566

0.7207

0.7380

0.7042

6

0.7813

0.7457

0.72

1.0000

0.5625

Avg.

0.7556

0.8383

0.7445

0.8056

0.7807

Std.

0.0247

0.3648

0.0732

0.1526

0.2423

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