Table 11 The average recall, precision and \(F_{1}\)-score of Iris-setosa data depending on the noise level (standard deviation in parentheses)

From: Norm ball classifier for one-class classification

Classifier Training Validation Test
Recall Precision \({F}_{1}\)-score Recall Precision \({F}_{1}\)-score Recall Precision \({F}_{1}\)-score
0%
Two norm 0.987 (0.02) 1.000 (0.00) 0.993 (0.01) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02)
Max norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02)
One norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.920 (0.12) 1.000 (0.00) 0.954 (0.07)
Mix norm 0.993 (0.01) 1.000 (0.00) 0.997 (0.01) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
MoG 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
PDE 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
1-NN 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
k-NN 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
SVDD 0.987 (0.03) 1.000 (0.00) 0.993 (0.01) 0.940 (0.08) 1.000 (0.00) 0.967 (0.04) 0.940 (0.08) 1.000 (0.00) 0.967 (0.04)
5%
Two norm 0.974 (0.01) 1.000 (0.00) 0.987 (0.01) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.940 (0.08) 1.000 (0.00) 0.967 (0.04)
Max norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.960 (0.05) 1.000 (0.00) 0.979 (0.03)
One norm 0.993 (0.01) 1.000 (0.00) 0.997 (0.01) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.920 (0.12) 1.000 (0.00) 0.954 (0.07)
Mix norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02)
MoG 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
PDE 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
1-NN 1.000 (0.00) 0.944 (0.02) 0.971 (0.01) 0.860 (0.10) 0.467 (0.17) 0.580 (0.12) 0.860 (0.08) 0.402 (0.08) 0.540 (0.06)
k-NN 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
SVDD 0.953 (0.02) 0.954 (0.03) 0.954 (0.02) 0.920 (0.07) 0.980 (0.04) 0.947 (0.05) 0.940 (0.08) 0.982 (0.04) 0.958 (0.04)
10%
Two norm 0.974 (0.01) 1.000 (0.00) 0.987 (0.01) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.940 (0.08) 1.000 (0.00) 0.967 (0.04)
Max norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.960 (0.05) 1.000 (0.00) 0.979 (0.03)
One norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02)
Mix norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.960 (0.05) 1.000 (0.00) 0.979 (0.03)
MoG 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
PDE 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
1-NN 1.000 (0.00) 0.893 (0.01) 0.943 (0.01) 0.860 (0.10) 0.439 (0.11) 0.573 (0.10) 0.860 (0.08) 0.426 (0.11) 0.558 (0.08)
k-NN 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
SVDD 0.800 (0.02) 1.000 (0.00) 0.889 (0.01) 0.840 (0.12) 1.000 (0.00) 0.908 (0.08) 0.780 (0.10) 1.000 (0.00) 0.873 (0.07)
15%
Two norm 0.974 (0.01) 1.000 (0.00) 0.987 (0.01) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.940 (0.08) 1.000 (0.00) 0.967 (0.04)
Max norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.960 (0.05) 1.000 (0.00) 0.979 (0.03)
One norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.940 (0.08) 1.000 (0.00) 0.967 (0.04)
Mix norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02)
MoG 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
PDE 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
1-NN 1.000 (0.00) 0.848 (0.01) 0.918 (0.01) 0.980 (0.04) 0.379 (0.06) 0.544 (0.07) 0.980 (0.04) 0.371 (0.06) 0.536 (0.07)
k-NN 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
SVDD 0.827 (0.02) 1.000 (0.00) 0.905 (0.01) 0.840 (0.14) 0.905 (0.13) 0.866 (0.12) 0.800 (0.11) 0.898 (0.16) 0.830 (0.08)
20%
Two norm 0.974 (0.01) 1.000 (0.00) 0.987 (0.01) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.940 (0.08) 1.000 (0.00) 0.967 (0.04)
Max norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.960 (0.05) 1.000 (0.00) 0.979 (0.03)
One norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02)
Mix norm 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02) 0.980 (0.04) 1.000 (0.00) 0.989 (0.02)
MoG 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
PDE 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
1-NN 1.000 (0.00) 0.794 (0.02) 0.885 (0.01) 0.760 (0.14) 0.518 (0.17) 0.609 (0.17) 0.800 (0.06) 0.382 (0.10) 0.510 (0.08)
k-NN 0.973 (0.01) 1.000 (0.00) 0.986 (0.01) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00) 1.000 (0.00)
SVDD 0.760 (0.03) 0.991 (0.02) 0.860 (0.02) 0.740 (0.14) 0.917 (0.17) 0.806 (0.13) 0.740 (0.14) 0.940 (0.12) 0.818 (0.11)
  1. The bolded value is the best within the group