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Table 4 The average AUC values–global, obtained for a particular fingerprint and particular target

From: Robust optimization of SVM hyperparameters in the classification of bioactive compounds

Fingerprint/target Bayes Random Grid search SVMlight libSVM
global 0.883* 0.870 0.799 0.676 0.792
EstateFP 0.847* 0.829 0.774 0.690 0.763
ExtFP 0.902* 0.891 0.806 0.669 0.874
KlekFP 0.899* 0.889 0.812 0.669 0.730
MACCSFP 0.890* 0.876 0.798 0.683 0.828
PubchemFP 0.898* 0.885 0.816 0.669 0.808
SubFP 0.864* 0.854 0.787 0.677 0.749
5-HT\(_\text {2A}\) 0.860* 0.850 0.780 0.683 0.743
5-HT\(_\text {2C}\) 0.848* 0.821 0.702 0.568 0.717
5-HT\(_\text {6}\) 0.913* 0.910 0.886 0.814 0.862
5-HT\(_\text {7}\) 0.830* 0.816 0.748 0.675 0.714
CDK2 0.876* 0.875 0.796 0.664 0.768
M\(_\text {1}\) 0.850* 0.843 0.778 0.557 0.748
ERK2 0.958 0.961* 0.949 0.931 0.942
AChE 0.884* 0.854 0.788 0.611 0.764
A\(_\text {1}\) 0.843* 0.835 0.764 0.564 0.720
alpha2AR 0.875* 0.874 0.773 0.563 0.725
beta1AR 0.910* 0.864 0.798 0.710 0.828
beta3AR 0.874* 0.823 0.826 0.545 0.722
CB1 0.874* 0.854 0.782 0.622 0.793
DOR 0.888* 0.880 0.734 0.599 0.814
D\(_\text {4}\) 0.841* 0.837 0.759 0.698 0.745
H\(_\text {1}\) 0.898* 0.880 0.638 0.548 0.801
H\(_\text {3}\) 0.937* 0.926 0.906 0.897 0.905
HIVi 0.939 0.945* 0.934 0.901 0.911
IR 0.936* 0.936* 0.925 0.886 0.897
ABL 0.850* 0.831 0.748 0.587 0.733
HLE 0.867* 0.865 0.763 0.578 0.779
  1. The highest values obtained among all strategies tested are marked with an asterisk sign