From: Deep transfer learning with fuzzy ensemble approach for the early detection of breast cancer
TL Models | Output Classes | Precision (%) | Recall (%) | F1 Score (%) | Overall Accuracy (%) |
---|---|---|---|---|---|
VGG11 | N | 95.013 | 96.284 | 96.149 | 95.833 |
B | 96.246 | 95.27 | 96.088 | ||
M | 96.271 | 95.946 | 96.113 | ||
VGG11 with Weighted Average | N | 95.333 | 96.622 | 96.225 | 96.059 |
B | 96.246 | 95.27 | 96.151 | ||
M | 96.611 | 96.284 | 96.202 | ||
VGG11 with Sugeno Integral | N | 95.667 | 96.959 | 96.479 | 96.396 |
B | 96.918 | 95.608 | 96.487 | ||
M | 96.622 | 96.622 | 97.395 | ||
VGG11 with Fuzzy Ranking using modified Gompertz Function | N | 96.346 | 97.973 | 97.474 | 97.072 |
B | 97.938 | 96.284 | 97.321 | ||
M | 96.959 | 96.959 | 97.386 | ||
Inception v3 | N | 95.973 | 96.622 | 96.224 | 96.284 |
B | 96.599 | 95.946 | 96.157 | ||
M | 96.284 | 96.284 | 96.183 | ||
Inception v3 with Weighted Average | N | 96.309 | 96.959 | 97.316 | 96.622 |
B | 96.622 | 96.622 | 97.259 | ||
M | 96.939 | 96.284 | 97.212 | ||
Inception v3 with Sugeno Integral | N | 96.333 | 97.635 | 97.498 | 97.072 |
B | 97.288 | 96.959 | 97.351 | ||
M | 97.611 | 96.622 | 97.333 | ||
Inception v3 with Fuzzy Ranking using modified Gompertz Function | N | 97.659 | 98.649 | 98.489 | 98.086 |
B | 98.305 | 97.973 | 98.392 | ||
M | 98.299 | 97.635 | 98.244 | ||
ResNet50 | N | 96.321 | 97.297 | 97.516 | 96.622 |
B | 96.928 | 95.946 | 96.773 | ||
M | 96.622 | 96.922 | 97.491 | ||
ResNet50 with Weighted Average | N | 96.333 | 97.635 | 97.689 | 96.847 |
B | 96.939 | 96.284 | 97.258 | ||
M | 97.279 | 96.622 | 97.614 | ||
ResNet50 with Sugeno Integral | N | 96.678 | 98.311 | 97.766 | 97.297 |
B | 97.279 | 96.622 | 97.369 | ||
M | 97.952 | 96.959 | 97.727 | ||
ResNet50 with Fuzzy Ranking using modified Gompertz Function | N | 98.986 | 98.986 | 98.916 | 98.986 |
B | 99.321 | 98.649 | 99.152 | ||
M | 98.658 | 99.324 | 99.298 |