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Table 5 Comparison of prediction error on data with noise for the different models

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