Table 3.

Performance of the hybrid learning-based classification model for different numbers of selected sensors evaluated using a 5-fold cross-validation and repeated 10 times. Similar performances in terms of accuracy, sensitivity, and specificity can be achieved by the models with 5 and 10 sensors, demonstrating the possibility of reducing the used sensor number in GeNose C19.

Number of sensors	Selected sensors	Accuracy (%)	Sensitivity (%)	Specificity (%)
2	S4, S9	78 ± 3	78 ± 6	78 ± 7
3	S4, S9, S10	83 ± 3	86 ± 4	80 ± 6
4	S4, S9, S10, S2	85 ± 3	89 ± 5	82 ± 6
5	S4, S9, S10, S2, S8	86 ± 3	88 ± 6	84 ± 6
6	S4, S9, S10, S2, S8, S3	85 ± 3	87 ± 6	83 ± 6
10	S1–S10	86 ± 3	87 ± 6	84 ± 6