Table 15 Performance comparison on obesity detection using various bio-inspired algorithms.
From: Bio inspired optimization techniques for disease detection in deep learning systems
Algorithm | Accuracy (%) | Precision (%) | Recall (%) | F1 Score (%) | Specificity (%) | Sensitivity (%) |
|---|---|---|---|---|---|---|
Particle Swarm Optimization (PSO)6 | 91.0 | 90.0 | 92.0 | 91.0 | 89.0 | 92.5 |
Artificial Bee Colony (ABC)12 | 89.0 | 88.0 | 90.0 | 89.0 | 86.5 | 90.5 |
Cuckoo Search (CS)34 | 92.0 | 91.0 | 93.0 | 92.0 | 90.0 | 93.5 |
Grey Wolf Optimizer (GWO)20 | 91.5 | 90.5 | 92.5 | 91.5 | 88.5 | 92.0 |
Dragonfly Algorithm (DA)49 | 87.0 | 86.0 | 88.5 | 87.2 | 84.0 | 89.0 |
Genetic Algorithms (GA)14 | 88.0 | 87.0 | 89.0 | 88.0 | 86.0 | 89.5 |
Ant Colony Optimization (ACO)60 | 86.0 | 85.0 | 87.0 | 86.0 | 83.5 | 87.5 |
Firefly Algorithm (FA)56 | 87.5 | 86.5 | 88.0 | 87.2 | 84.5 | 88.5 |
Bat Algorithm (BA)23 | 88.5 | 87.5 | 89.5 | 88.5 | 85.5 | 89.0 |
Whale Optimization Algorithm (WOA)27 | 89.5 | 88.5 | 90.5 | 89.5 | 86.0 | 91.0 |
