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Table 3:
GP surrogate model parameters. Results from the combination of n-way ANOVA analysis without interactions and the posthoc Tukey–Kramer's comparison tests of the effects of four parameters on the mean of RDEμ/rsucc. The table shows the values of the parameters sorted according to the corresponding regressed RDEμ/rsucc (shown left) for the respective combinations of dimension and half of the optimization run. Values with the mean response according to Tukey–Kramer significantly higher than the respective lowest mean response are marked with . Stars after the values sign the statistical significance of rejecting the ANOVA test hypotheses that the effects of the respective parameters on the mean responses of RDEμ/rsucc are negligible. Significant results of Tukey–Kramer's comparisons between the values of the respective parameters are marked in the gray lines of each block (1 = best value, 2 = second etc.). Stars // sign the p-value lower than 0.05/0.01/0.001 for the respective tests.
dimPart of RunTrainset SelectionrmaxANmaxCovariance Function
2-D 0.40 k-NN (TSS2) 0.41 0.40 20·D 0.40 KMate´rnν=5/2 
  0.41 population (TSS4) 0.41 0.41 15·D 0.41 KMate´rnν=3/2 
  0.41 clustering (TSS3)   0.41 10·D 0.41 KSE 
  0.41 recent (TSS1)       
2-D ii 0.42 k-NN (TSS2) 0.42 2 0.42 20·D 0.42 KSE 
  0.42 recent (TSS1) 0.42 4  0.42 15·D 0.42 KMate´rnν=5/2 
  0.42 clustering (TSS3)   0.42 10·D 0.42 KMate´rnν=3/2 
  0.42 population (TSS4)       
   1<  
3-D 0.38 recent (TSS1) 0.38 0.38 15·D 0.38 KMate´rnν=3/2 
  0.38 k-NN (TSS2) 0.39 0.38 10·D 0.38 KMate´rnν=5/2 
  0.38 clustering (TSS3)   0.38 20·D 0.39 KSE 
  0.39 population (TSS4)       
3-D ii 0.38 recent (TSS1) 0.39 0.39 15·D 0.39 KMate´rnν=3/2 
  0.39 k-NN (TSS2) 0.39 0.39 10·D 0.39 KMate´rnν=5/2 
  0.39 clustering (TSS3)    0.39 20·D 0.40 KSE 
  0.40 population (TSS4)        
  1<3, 1<4, 2<   
5-D 0.34 k-NN (TSS2) 0.34 2 0.34 10·D 0.34 KMate´rnν=3/2 
  0.34 recent (TSS1) 0.35 4  0.34 15·D 0.34 KMate´rnν=5/2 
  0.34 clustering (TSS3)   0.34 20·D 0.35 KSE 
  0.35 population (TSS4)        
  1<4, 2<4, 3<1< 1<3, 2<
5-D ii 0.35 k-NN (TSS2) 0.35 2 0.35 15·D 0.35 KMate´rnν=5/2 
  0.35 recent (TSS1) 0.36 4  0.35 10·D 0.35 KMate´rnν=3/2 
  0.35 clustering (TSS3)   0.35 20·D 0.36 KSE 
  0.37 population (TSS4)        
  1<4, 2<4, 3<1< 1<3, 2<
10-D 0.34 k-NN (TSS2) 0.33 4 0.34 20·D 0.33 KMate´rnν=5/2 
  0.34 recent (TSS1) 0.35 2  0.34 15·D 0.34 KSE 
  0.34 clustering (TSS3)    0.34 10·D 0.35 KMate´rnν=3/2 
  0.35 population (TSS4)        
  1<3, 1<4, 2<1< 1<2, 1<
10-D ii 0.32 k-NN (TSS2) 0.32 4 0.33 20·D 0.33 KMate´rnν=5/2 
  0.33 recent (TSS1)  0.34 2  0.33 15·D 0.34 KSE 
  0.34 clustering (TSS3)    0.34 10·D 0.34 KMate´rnν=3/2 
  0.34 population (TSS4)        
  1<2, 1<3, 1<1< 1<2, 1<
20-D 0.35 k-NN (TSS2) 0.34 4 0.35 20·D 0.34 KMate´rnν=5/2 
  0.36 population (TSS4)  0.37 2  0.35 15·D 0.34 KMate´rnν=3/2 
  0.36 clustering (TSS3)    0.36 10·D 0.39 KSE 
  0.36 recent (TSS1)        
  1<2, 1<3, 1<1<1<3, 2<1<2, 1<3, 
     2<
20-D ii 0.34 k-NN (TSS2) 0.33 4 0.34 20·D 0.32 KMate´rnν=5/2 
  0.35 recent (TSS1)  0.36 2  0.35 15·D 0.34 KMate´rnν=3/2 
  0.35 population (TSS4)    0.36 10·D 0.38 KSE 
  0.36 clustering (TSS3)        
  1<2, 1<3, 1<4, 2<1<1<3, 2<1<2, 1<3, 
     2<
dimPart of RunTrainset SelectionrmaxANmaxCovariance Function
2-D 0.40 k-NN (TSS2) 0.41 0.40 20·D 0.40 KMate´rnν=5/2 
  0.41 population (TSS4) 0.41 0.41 15·D 0.41 KMate´rnν=3/2 
  0.41 clustering (TSS3)   0.41 10·D 0.41 KSE 
  0.41 recent (TSS1)       
2-D ii 0.42 k-NN (TSS2) 0.42 2 0.42 20·D 0.42 KSE 
  0.42 recent (TSS1) 0.42 4  0.42 15·D 0.42 KMate´rnν=5/2 
  0.42 clustering (TSS3)   0.42 10·D 0.42 KMate´rnν=3/2 
  0.42 population (TSS4)       
   1<  
3-D 0.38 recent (TSS1) 0.38 0.38 15·D 0.38 KMate´rnν=3/2 
  0.38 k-NN (TSS2) 0.39 0.38 10·D 0.38 KMate´rnν=5/2 
  0.38 clustering (TSS3)   0.38 20·D 0.39 KSE 
  0.39 population (TSS4)       
3-D ii 0.38 recent (TSS1) 0.39 0.39 15·D 0.39 KMate´rnν=3/2 
  0.39 k-NN (TSS2) 0.39 0.39 10·D 0.39 KMate´rnν=5/2 
  0.39 clustering (TSS3)    0.39 20·D 0.40 KSE 
  0.40 population (TSS4)        
  1<3, 1<4, 2<   
5-D 0.34 k-NN (TSS2) 0.34 2 0.34 10·D 0.34 KMate´rnν=3/2 
  0.34 recent (TSS1) 0.35 4  0.34 15·D 0.34 KMate´rnν=5/2 
  0.34 clustering (TSS3)   0.34 20·D 0.35 KSE 
  0.35 population (TSS4)        
  1<4, 2<4, 3<1< 1<3, 2<
5-D ii 0.35 k-NN (TSS2) 0.35 2 0.35 15·D 0.35 KMate´rnν=5/2 
  0.35 recent (TSS1) 0.36 4  0.35 10·D 0.35 KMate´rnν=3/2 
  0.35 clustering (TSS3)   0.35 20·D 0.36 KSE 
  0.37 population (TSS4)        
  1<4, 2<4, 3<1< 1<3, 2<
10-D 0.34 k-NN (TSS2) 0.33 4 0.34 20·D 0.33 KMate´rnν=5/2 
  0.34 recent (TSS1) 0.35 2  0.34 15·D 0.34 KSE 
  0.34 clustering (TSS3)    0.34 10·D 0.35 KMate´rnν=3/2 
  0.35 population (TSS4)        
  1<3, 1<4, 2<1< 1<2, 1<
10-D ii 0.32 k-NN (TSS2) 0.32 4 0.33 20·D 0.33 KMate´rnν=5/2 
  0.33 recent (TSS1)  0.34 2  0.33 15·D 0.34 KSE 
  0.34 clustering (TSS3)    0.34 10·D 0.34 KMate´rnν=3/2 
  0.34 population (TSS4)        
  1<2, 1<3, 1<1< 1<2, 1<
20-D 0.35 k-NN (TSS2) 0.34 4 0.35 20·D 0.34 KMate´rnν=5/2 
  0.36 population (TSS4)  0.37 2  0.35 15·D 0.34 KMate´rnν=3/2 
  0.36 clustering (TSS3)    0.36 10·D 0.39 KSE 
  0.36 recent (TSS1)        
  1<2, 1<3, 1<1<1<3, 2<1<2, 1<3, 
     2<
20-D ii 0.34 k-NN (TSS2) 0.33 4 0.34 20·D 0.32 KMate´rnν=5/2 
  0.35 recent (TSS1)  0.36 2  0.35 15·D 0.34 KMate´rnν=3/2 
  0.35 population (TSS4)    0.36 10·D 0.38 KSE 
  0.36 clustering (TSS3)        
  1<2, 1<3, 1<4, 2<1<1<3, 2<1<2, 1<3, 
     2<
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