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Figure 7 shows the average classifications for the datasets using each of the descriptors.

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Average classification accuracy.

Figure 7 Average classification accuracy over the three datasets.

The average classification and precision-recall results are reported.

However, average classification accuracy decreases when taking k2 into account.

Horizontal axis: input instances, vertical axis: average classification time (seconds).

Average classification accuracy is measured as the performance metric.

Table 3 Average classification accuracy for direct versus hierarchical approaches.

The average classification accuracy of web break cases was equal to 76.7%.

Average classification accuracy of 93.0% is achieved using a deep LSTM architecture.

Random selection maintained an average classification accuracy rate above 85%% for 10 50 electrodes and obtained the highest average classification accuracy rate of 89.6 % with 32 electrodes.

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