Table 4.
Experimental results using animal dataset.
| ANN Algorithm | DT Algorithm | Proposed H-DNN Algorithm | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IR | Acc | SP | SE | F1 | Prec | Acc | SE | SP | F1 | Prec | Acc | SE | SP | F1 | Prec |
| 1 | 0.51 | 0.03 | 1.00 | 0.37 | 0.73 | 0.57 | 0.49 | 0.96 | 0.65 | 0.83 | 0.93 | 0.94 | 0.93 | 0.93 | 0.93 |
| 100 | 0.99 | 0.99 | 0.66 | 0.74 | 0.69 | 0.99 | 0.81 | 0.83 | 0.78 | 0.76 | 0.99 | 0.64 | 1.00 | 0.82 | 0.82 |
| 500 | 1.00 | 1.00 | 0.53 | 0.50 | 0.50 | 1.00 | 0.72 | 0.77 | 0.60 | 0.59 | 1.00 | 0.44 | 1.00 | 0.70 | 0.68 |
| 1,000 | 1.00 | 1.00 | 0.67 | 0.50 | 0.50 | 1.00 | 0.71 | 0.83 | 0.59 | 0.59 | 1.00 | 0.41 | 1.00 | 0.69 | 0.67 |
| 1,500 | 1.00 | 1.00 | 0.60 | 0.50 | 0.50 | 1.00 | 0.71 | 0.80 | 0.61 | 0.61 | 1.00 | 0.41 | 1.00 | 0.72 | 0.73 |
| 2,000 | 1.00 | 1.00 | 0.44 | 0.50 | 0.50 | 1.00 | 0.63 | 0.72 | 0.57 | 0.58 | 1.00 | 0.26 | 1.00 | 0.64 | 0.65 |
| 2,500 | 1.00 | 1.00 | 0.45 | 0.50 | 0.50 | 1.00 | 0.58 | 0.73 | 0.54 | 0.55 | 1.00 | 0.15 | 1.00 | 0.58 | 0.59 |
| 3,000 | 1.00 | 1.00 | 0.33 | 0.50 | 0.50 | 1.00 | 0.63 | 0.67 | 0.58 | 0.60 | 1.00 | 0.26 | 1.00 | 0.66 | 0.69 |
| 3,500 | 1.00 | 1.00 | 0.13 | 0.50 | 0.50 | 1.00 | 0.60 | 0.56 | 0.55 | 0.55 | 1.00 | 0.20 | 1.00 | 0.60 | 0.60 |
| 4,000 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | 1.00 | 0.50 | 0.50 | 0.50 | 0.50 | 1.00 | 0.00 | 1.00 | 0.50 | 0.50 |
| 4,500 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | 1.00 | 0.50 | 0.50 | 0.50 | 0.50 | 1.00 | 0.00 | 1.00 | 0.50 | 0.50 |
| 5,000 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | 1.00 | 0.55 | 0.50 | 0.52 | 0.52 | 1.00 | 0.10 | 1.00 | 0.55 | 0.55 |