Skip to main content

Table 3 Evaluation of classification algorithms

From: Prediction of lymphedema occurrence in patients with breast cancer using the optimized combination of ensemble learning algorithm and feature selection

Classification
Evaluation Confusion Matrix Algorithm
FPR = 0. 2500 143 547 SVM (Linear)
FRR = 0. 2072
Accuracy = 0. 7706 555 185
Cost = 0. 2291
FPR = 0. 1486 53 637 SVM (RBF)
FRR = 0. 0768
Accuracy = 0. 8860 630 110
Cost = 0. 1135
FPR = 0. 2365 22 668 SVM (Polynomial)
FRR = 0. 3190
Accuracy = 0. 8622 565 175
Cost = 0. 1363
FPR = 0. 2757 142 548 LDA
FRR = 0. 2058
Accuracy = 0. 7580 536 204
Cost = 0. 2415
FPR = 0. 3959 71 619 KNN
FRR = 0. 1029
Accuracy = 0. 7455 447 293
Cost = 0. 2525
FPR = 0. 4514 120 570 Bayes
FRR = 0. 1739
Accuracy = 0. 6825 406 334
Cost = 0. 3155
FPR = 0. 1622 138 552 C5
FRR = 0. 2000
Accuracy = 0. 8196 620 120
Cost = 0. 1807
FPR = 0. 2216 189 501 MLP
FRR = 0. 2739
Accuracy = 0. 7531 576 164
Cost = 0. 2472