Table 3 Classification accuracies and efficiencies of support vector machine models by the kernel function.
From: Performance and efficiency of machine learning algorithms for analyzing rectangular biomedical data
Kernel function | Alive (%) | Non-breast cancer (%) | Breast cancer (%) | CVS (%) | Other cause (%) | Total accuracy (%) | Run-time (s) |
|---|---|---|---|---|---|---|---|
Linear | 96.22 | 0.00 | 39.43 | 0.00 | 0.00 | 69.06 | 175.50 |
Radial basis function | 95.60 | 1.26 | 6.23 | 1.29 | 6.27 | 63.86 | 286.31 |
Gaussian | 95.60 | 1.26 | 6.23 | 1.29 | 6.27 | 63.86 | 290.28 |
Polynomial | 27.75 | 3.14 | 32.79 | 13.83 | 36.51 | 27.46 | 3710.50 |
