From: Supervised learning methods in modeling of CD4+ T cell heterogeneity
Noise level | Approach | IL17 | RORgt | IFNγ | Tbet | FOXP3 | Sum of prediction error |
---|---|---|---|---|---|---|---|
Uniformly distributed noise in range of [−0.5 %, 0.5 %] | Artificial Neural Network | 0.0671 | 0.0698 | 0.042 | 0.0362 | 0.0354 | 0.250 |
Linear Regression | 0.235 | 0.235 | 0.190 | 0.129 | 0.0355 | 0.824 | |
Support Vector Machine | 0.0329 | 0.146 | 0.182 | 0.178 | 0.111 | 0.649 | |
Random Forest | 0.0413 | 0.0479 | 0.0364 | 0.0769 | 0.0397 | 0.242 | |
Uniformly distributed noise in range of [−1 %, 1 %] | Artificial Neural Network | 0.0706 | 0.0553 | 0.0435 | 0.0361 | 0.0393 | 0.2448 |
Linear Regression | 0.795 | 0.682 | 0.677 | 0.546 | 0.46 | 3.16 | |
Support Vector Machine | 0.179 | 0.177 | 0.147 | 0.112 | 0.0406 | 0.6556 | |
Random Forest | 0.0552 | 0.0495 | 0.0484 | 0.0935 | 0.0349 | 0.2815 |