Training dataset
|
Feature
|
Tested datasets
|
---|
| |
BNCPCS
|
DC
|
Bahadur
|
Ponstingl
|
---|
BNCPCS
|
ΣB
|
0.93(0.97)
|
0.32(0.65)
|
0.65(0.82)
|
0.82(0.91)
|
|
ΔASA
|
0.92(0.96)
|
-0.18(0.47)
|
0.59(0.78)
|
0.73(0.86)
|
|
avgΣB
|
0.92(0.96)
|
0.37(0.68)
|
0.64(0.82)
|
0.80(0.90)
|
|
avgNo.B
|
0.95(0.98)
|
0.25(0.60)
|
0.70(0.84)
|
0.84(0.92)
|
|
avgΣB*avgNo.B
|
0.94(0.97)
|
0.33(0.66)
|
0.70(0.85)
|
0.82(0.91)
|
|
avgΔASA
|
0.91(0.96)
|
-0.16(0.48)
|
0.64(0.81)
|
0.72(0.86)
|
DC
|
ΣB
|
0.85(0.92)
|
0.38(0.69)
|
0.68(0.85)
|
0.81(0.90)
|
|
ΔASA
|
0.73(0.86)
|
0.15(0.57)
|
0.66(0.84)
|
0.62(0.80)
|
|
avgΣB
|
0.88(0.94)
|
0.45(0.73)
|
0.73(0.87)
|
0.80(0.90)
|
|
avgNo.B
|
0.80(0.90)
|
0.46(0.72)
|
0.74(0.87)
|
0.70(0.84)
|
|
avgΣB*avgNo.B
|
0.86(0.93)
|
0.45(0.73)
|
0.75(0.88)
|
0.81(0.90)
|
|
avgΔASA
|
0.76(0.88)
|
0.27(0.63)
|
0.68(0.85)
|
0.66(0.82)
|
Bahadur
|
ΣB
|
0.84(0.92)
|
0.38(0.69)
|
0.71(0.86)
|
0.79(0.89)
|
|
ΔASA
|
0.73(0.86)
|
0.15(0.57)
|
0.66(0.84)
|
0.62(0.80)
|
|
avgΣB
|
0.84(0.92)
|
0.41(0.70)
|
0.75(0.88)
|
0.81(0.90)
|
|
avgNo.B
|
0.86(0.93)
|
0.33(0.66)
|
0.75(0.88)
|
0.77(0.88)
|
|
avgΣB*avgNo.B
|
0.88(0.94)
|
0.45(0.73)
|
0.77(0.89)
|
0.83(0.91)
|
|
avgΔASA
|
0.81(0.90)
|
0.21(0.60)
|
0.69(0.85)
|
0.69(0.84)
|
Ponstingl
|
ΣB
|
0.88(0.94)
|
0.39(0.70)
|
0.69(0.85)
|
0.81(0.90)
|
|
ΔASA
|
0.91(0.96)
|
-0.18(0.47)
|
0.59(0.79)
|
0.72(0.86)
|
|
avgΣB
|
0.90(0.95)
|
0.43(0.71)
|
0.73(0.87)
|
0.82(0.91)
|
|
avgNo.B
|
0.95(0.98)
|
0.25(0.60)
|
0.70(0.84)
|
0.84(0.92)
|
|
avgΣB*avgNo.B
|
0.90(0.95)
|
0.40(0.70)
|
0.75(0.88)
|
0.83(0.92)
|
|
avgΔASA
|
0.92(0.96)
|
-0.19(0.46)
|
0.65(0.82)
|
0.78(0.89)
|
PDBbind
|
ΣB
|
0.93(0.97)
|
0.38(0.68)
|
0.62(0.79)
|
0.72(0.86)
|
|
ΔASA
|
0.88(0.94)
|
-0.16(0.48)
|
0.49(0.68)
|
0.62(0.79)
|
|
avgΣB
|
0.88(0.94)
|
0.41(0.71)
|
0.71(0.86)
|
0.83(0.92)
|
|
avgNo.B
|
0.92(0.96)
|
0.38(0.68)
|
0.74(0.88)
|
0.80(0.90)
|
|
avgΣB*avgNo.B
|
0.90(0.95)
|
0.38(0.69)
|
0.76(0.88)
|
0.86(0.93)
|
|
avgΔASA
|
0.88(0.94)
|
0.02(0.51)
|
0.66(0.84)
|
0.70(0.85)
|
- X.XX(Y.YY) represent the classification performances where X.XX is the MCC score and Y.YY is the accuracy score. The italic numbers are the learning performances, and thus they are not used in the comparison. The bold-font numbers are the better performances when comparing ΣB and avgΣB*avgNo.B with ΔASA, and ΣB with ΔASA.