Table 5.
Experimental results using plant 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 | 1.00 | 0.96 | 0.99 | 0.98 | 0.73 | 0.97 | 0.96 | 0.97 | 0.97 | 0.95 | 0.94 | 0.97 | 0.95 | 0.95 |
| 100 | 0.99 | 1.00 | 0.55 | 0.76 | 0.49 | 0.99 | 0.88 | 0.77 | 0.82 | 0.68 | 1.00 | 0.77 | 1.00 | 0.87 | 0.87 |
| 500 | 1.00 | 1.00 | 0.36 | 0.50 | 0.50 | 1.00 | 0.79 | 0.68 | 0.63 | 0.62 | 1.00 | 0.58 | 1.00 | 0.76 | 0.74 |
| 1,000 | 1.00 | 1.00 | 0.45 | 0.50 | 0.50 | 1.00 | 0.77 | 0.73 | 0.61 | 0.59 | 1.00 | 0.53 | 1.00 | 0.71 | 0.67 |
| 1,500 | 1.00 | 1.00 | 0.54 | 0.50 | 0.50 | 1.00 | 0.67 | 0.77 | 0.58 | 0.57 | 1.00 | 0.33 | 1.00 | 0.65 | 0.64 |
| 2,000 | 1.00 | 1.00 | 0.50 | 0.50 | 0.50 | 1.00 | 0.68 | 0.75 | 0.60 | 0.61 | 1.00 | 0.36 | 1.00 | 0.70 | 0.73 |
| 2,500 | 1.00 | 1.00 | 0.33 | 0.50 | 0.50 | 1.00 | 0.64 | 0.67 | 0.57 | 0.57 | 1.00 | 0.27 | 1.00 | 0.64 | 0.64 |
| 3,000 | 1.00 | 1.00 | 0.11 | 0.50 | 0.50 | 1.00 | 0.71 | 0.56 | 0.57 | 0.55 | 1.00 | 0.43 | 1.00 | 0.64 | 0.61 |
| 3,500 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | 1.00 | 0.80 | 0.50 | 0.61 | 0.58 | 1.00 | 0.60 | 1.00 | 0.71 | 0.67 |
| 4,000 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | 1.00 | 0.80 | 0.50 | 0.62 | 0.61 | 1.00 | 0.60 | 1.00 | 0.75 | 0.71 |
| 4,500 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | 1.00 | 0.58 | 0.50 | 0.54 | 0.54 | 1.00 | 0.17 | 1.00 | 0.58 | 0.58 |
| 5,000 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | 1.00 | 0.61 | 0.50 | 0.56 | 0.56 | 1.00 | 0.22 | 1.00 | 0.61 | 0.61 |