Table 3 Comparative analysis of SSODE-GCNDM approach with recent models59,60,61,62,63.
Classifiers | \(\:\varvec{A}\varvec{c}\varvec{c}{\varvec{u}}_{\varvec{y}}\) | \(\:\varvec{P}\varvec{r}\varvec{e}{\varvec{c}}_{\varvec{n}}\) | \(\:\varvec{R}\varvec{e}\varvec{c}{\varvec{a}}_{\varvec{l}}\) | \(\:{\varvec{F}}_{\varvec{m}\varvec{e}\varvec{a}\varvec{s}\varvec{u}\varvec{r}\varvec{e}}\) |
|---|---|---|---|---|
LR | 91.10 | 91.00 | 91.00 | 91.00 |
KNN | 97.00 | 97.00 | 97.00 | 97.00 |
RF | 98.54 | 98.52 | 98.22 | 98.79 |
DT | 98.36 | 98.64 | 98.24 | 97.82 |
AdaBoost | 98.09 | 98.08 | 98.24 | 98.35 |
XGBoost | 98.34 | 98.65 | 98.51 | 98.46 |
MLP Classifier | 98.98 | 98.67 | 98.47 | 98.61 |
DNN | 99.37 | 99.17 | 98.97 | 98.82 |
QCNN | 99.25 | 99.12 | 99.15 | 98.59 |
COA-GS-IDNN | 98.71 | 99.41 | 98.48 | 98.70 |
GWO-LSTM | 99.10 | 98.87 | 98.70 | 98.82 |
AE | 98.95 | 98.82 | 99.17 | 98.82 |
SSODE-GCNDM | 99.62 | 99.72 | 99.62 | 99.67 |
