Table 5 Precision, recall, and F1 score of the 7 classifiers for 4 cases
ML techniques | PDs vs. Cons (with 36 features) | PDs vs. Cons (with 5 features) | F vs. NF (with 36 features) | F vs. NF (with 6 features) | |
|---|---|---|---|---|---|
Precision | LR | 97.6 ± 2.5 | 98.2 ± 2.6 | 74.2 ± 1.8 | 73.6 ± 10.7 |
KNN | 95.6 ± 5.3 | 97.1 ± 3.4 | 65.6 ± 9.7 | 67.4 ± 11.2 | |
NB | 91.9 ± 3.1 | 97.1 ± 2.9 | 74.3 ± 4.0 | 65.1 ± 9.7 | |
LDA | 96.3 ± 4.2 | 97.7 ± 3.2 | 72.6 ± 9.2 | 70.1 ± 12.1 | |
QDA | 98.2 ± 2.6 | 97.6 ± 2.5 | 73.3 ± 11.5 | 68.2 ± 10.6 | |
SVM | 98.2 ± 2.6 | 98.2 ± 2.6 | 72.1 ± 11.1 | 59.0 ± 33.6 | |
RF | 98.2 ± 1.7 | 98.2 ± 2.6 | 81.4 ± 6.6 | 71.6 ± 10.3 | |
Recall | LR | 97.4 ± 2.8 | 98.0 ± 3.0 | 72.8 ± 0.8 | 72.9 ± 10.8 |
KNN | 94.7 ± 6.9 | 96.7 ± 4.1 | 62.9 ± 8.7 | 61.9 ± 7.8 | |
NB | 91.6 ± 2.9 | 96.7 ± 3.3 | 70.6 ± 6.5 | 64.0 ± 9.0 | |
LDA | 96.1 ± 4.3 | 97.4 ± 3.6 | 71.8 ± 9.3 | 69.6 ± 12.3 | |
QDA | 98.0 ± 3.0 | 97.4 ± 2.8 | 72.6 ± 11.5 | 67.5 ± 10.9 | |
SVM | 98.0 ± 3.0 | 98.0 ± 3.0 | 69.4 ± 8.9 | 63.4 ± 16.8 | |
RF | 98.1 ± 1.8 | 98.0 ± 3.0 | 79.4 ± 6.9 | 70.8 ± 10.6 | |
F1 score | LR | 97.4 ± 2.8 | 98.0 ± 3.0 | 72.5 ± 0.9 | 72.7 ± 10.9 |
KNN | 94.6 ± 7.1 | 96.7 ± 4.1 | 61.6 ± 8.5 | 58.8 ± 8.7 | |
NB | 91.6 ± 2.8 | 96.7 ± 3.3 | 69.1 ± 9.2 | 63.5 ± 9.0 | |
LDA | 96.1 ± 4.3 | 97.4 ± 3.6 | 71.5 ± 9.4 | 69.5 ± 12.4 | |
QDA | 98.0 ± 3.0 | 97.4 ± 2.8 | 72.4 ± 11.6 | 67.2 ± 11.2 | |
SVM | 98.0 ± 3.0 | 98.0 ± 3.0 | 68.8 ± 8.8 | 54.9 ± 24.7 | |
RF | 98.1 ± 1.8 | 98.0 ± 3.0 | 79.1 ± 7.1 | 70.4 ± 10.9 |