Table 4 Performance of the probability calibration-based algorithms

NB

15.711 (13.557–17.914)

34.350 (29.275–39.800)

0.212 (0.199–0.228)

< 0.001(< 0.001- < 0.001)

NB-Platt

9.008 (7.919–10.647)

21.550 (17.475–25.800)

0.189 (0.181–0.197)

0.179 (0.055–0.389)

NB-IsoReg

9.820 (7.740–12.190)

40.000 (23.475–57.100)

0.208 (0.195–0.227)

< 0.001(< 0.001–0.057)

NB-RPR

8.743 (7.397–10.307)

21.600 (17.575–25.700)

0.189 (0.182–0.197)

0.191 (0.051–0.431)

LR

8.517 (7.244–10.093)

20.100 (16.675–25.025)

0.188 (0.180–0.196)

0.152 (0.022–0.403)

LR-Platt

8.981 (7.478–10.485)

20.900 (17.300–25.325)

0.189 (0.182–0.196)

0.215 (0.065–0.437)

LR-IsoReg

9.140 (6.970–11.810)

31.550 (20.000–50.175)

0.204 (0.193–0.220)

0.008(< 0.001–0.348)

LR-RPR

8.744 (7.308–10.143)

20.300 (16.700–24.425)

0.187 (0.181–0.194)

0.255 (0.092–0.507)

RF

12.740 (10.910–14.336)

27.200 (23.375–31.925)

0.201 (0.190–0.211)

< 0.001(< 0.001- < 0.001)

RF-Platt

8.998 (7.518–10.447)

21.100 (17.500–26.700)

0.192 (0.184–0.200)

0.156 (0.030–0.435)

RF-IsoReg

9.292 (7.332–11.353)

27.850 (20.000–40.000)

0.201 (0.191–0.215)

< 0.001(< 0.001–0.131)

RF-RPR

8.949 (7.387–10.524)

20.900 (17.400–26.025)

0.189 (0.182–0.196)

0.194 (0.061–0.458)

SVM

9.872 (8.317–11.777)

23.800 (19.000–28.925)

0.194 (0.185–0.204)

0.016(< 0.001–0.117)

SVM-Platt

9.077 (7.702–10.895)

21.750 (17.600–27.300)

0.192 (0.184–0.201)

0.169 (0.029–0.412)

SVM-IsoReg

9.501 (7.332–12.453)

30.350 (20.000–42.200)

0.205 (0.194–0.221)

0.003(< 0.001–0.249)

SVM-RPR

8.796 (7.362–10.439)

21.000 (16.775–26.550)

0.190 (0.183–0.199)

0.211 (0.064–0.471)

FFNN

8.238 (6.805–9.611)

20.150 (16.600–24.500)

0.184 (0.177–0.192)

0.244 (0.075–0.518)

FFNN-Platt

8.991 (7.721–10.642)

20.950 (16.875–26.100)

0.186 (0.179–0.194)

0.192 (0.056–0.425)

FFNN-IsoReg

10.866 (8.603–13.347)

40.550 (27.800–57.025)

0.211 (0.196–0.230)

< 0.001(< 0.001–0.003)

FFNN-RPR

8.703 (7.393–10.361)

21.400 (17.700–26.025)

0.185 (0.178–0.193)

0.227 (0.073–0.473)