Data | Â | Â | WISN | Maximum |
---|---|---|---|---|
Partitioning | Classification | Image | Parameter | F1-score |
Scheme | Algorithm | Representation | Setting | (%) |
Random | Support | Gray Scale | \(s = 125, q = [1, 1]\)#8 | 98 |
 | Vector | Red Channel | \(s = 100, q = [4, 1]\)#5 | 94 |
 | Machine | Green Channel | \(s = 75, q = [1, 1]\)#33 | 91 |
 |  | Blue Channel | \(s = 125, q = [3, 1]\)#10 | 82 |
 | Logistic | Green Channel | \(s = 125, q = [1, 1]\)#8 | 85 |
 | Regression | Gray Scale | \(s = 100, q = [3, 2]\)#4 | 82 |
 |  | Blue Channel | \(s = 125, q = [1, 1]\)#8 | 80 |
 |  | Red Channel | \(s = 125, q = [4, 1]\)#12 | 79 |
 | Convolutional | NA | Red Channel | 82 |
 | Neural |  |  |  |
 | Network |  |  |  |
Hospital | Support | Gray Scale | \(s = 125, q = [1, 1]\)#8 | 89 |
 | Vector | Blue Channel | \(s = 125, q = [4, 1]\)#37 | 86 |
 | Machine | Red Channel | \(s = 100, q = [4, 1]\)#5 | 85 |
 |  | Green Channel | \(s = 125, q = [2, 1]\)#9 | 83 |
 | Logistic | Red Channel | \(s = 125, q = [3, 2]\)#11 | 82 |
 | Regression | Gray Scale | \(s = 125, q = [4, 3]\)#14 | 77 |
 |  | Green Channel | \(s = 150, q = [4, 2]\)#31 | 72 |
 |  | Blue Channel | \(s = 150, q = [3, 2]\)#29 | 67 |
 | Convolutional | NA | Blue Channel | 83 |
 | Neural |  |  |  |
 | Network |  |  |  |