Table 2 Evaluation of the classifiers for each group and comparison among KNN, Random Forest, Naïve Bayes and Support Vector Machine
Groups | Sensitivity (± STD) | Specificity (± STD) | Precision (± STD) | Accuracy (± STD) |
|---|---|---|---|---|
KNN | ||||
 AG | 0.9737 (0.0582) | 0.9756 (0.0221) | 0.9320 (0.0566) | 0.9701 (0.0219) |
 MG | 0.8703 (0.0793) | 0.9897 (0.0142) | 0.9676 (0.0425) | 0.9599 (0.0221) |
 CG | 0.9769 (0.0265) | 0.9411 (0.0398) | 0.9445 (0.0353) | 0.9590 (0.0234) |
Random forest | ||||
 AG | 0.6852 (0.0030) | 0.8839 (0.0011) | 0.6642 (0.0021) | 0.8342 (0.0009) |
 MG | 0.6650 (0.0030) | 0.8961 (0.0009) | 0.6817 (0.0021) | 0.8383 (0.0009) |
 CG | 0.7900 (0.0018) | 0.7951 (0.0018) | 0.7947 (0.0014) | 0.7926 (0.0011) |
Naïve Bayes | ||||
 AG | 0.7132 (0.0052) | 0.8634 (0.0022) | 0.6391 (0.0040) | 0.8258 (0.0020) |
 MG | 0.5601 (0.0056) | 0.9424 (0.0018) | 0.7716 (0.0055) | 0.8468 (0.0018) |
 CG | 0.8411 (0.0029) | 0.7691 (0.0033) | 0.7864 (0.0024) | 0.8051 (0.0020) |
Support vector machine | ||||
 AG | 0.7942 (0.0049) | 0.7894 (0.0045) | 0.7925 (0.0040) | 0.7918 (0.0037) |
 MG | 0.7894 (0.0045) | 0.7942 (0.0049) | 0.7963 (0.0042) | 0.7918 (0.0037) |
 CG | 0.8846 (0.0030) | 0.7718 (0.0050) | 0.7989 (0.0037) | 0.8282 (0.0029) |