Skip to main content

Table 4 Average F1 scores on different N values. The values in brackets represent the standard deviation (Std) in 5-fold cross validation. The proposed SASMOTE algorithms perform better on the average F1 score with respect to the value of N = 1, 2, 3, 5 while B-SMOTE performs better with respect to the value of N = 4

From: A self-inspected adaptive SMOTE algorithm (SASMOTE) for highly imbalanced data classification in healthcare

Model

\(\boldsymbol{N = 1}\) (Std)

\(\boldsymbol{N = 2}\) (Std)

\(\boldsymbol{N = 3}\) (Std)

\(\boldsymbol{N = 4}\) (Std)

\(\boldsymbol{N = 5}\) (Std)

SASMOTE

47.04 (7.22)

51.32 (7.70)

51.88 (6.60)

51.13 (8.51)

51.16 (6.32)

SASMOTE w/o visible

48.97 (7.90)

49.60 (10.14)

48.04 (8.48)

50.15 (8.55)

49.72 (9.67)

SASMOTE w/o inspection

48.85 (4.60)

48.30 (6.90)

53.34 (6.92)

46.56 (8.90)

50.26 (11.94)

B-SMOTE

44.76 (7.85)

49.37 (10.60)

49.31 (7.76)

51.17 (10.53)

47.80 (8.12)

SMOTE

45.59 (8.90)

46.31 (9.71)

47.72 (11.81)

50.03 (7.92)

46.07 (11.19)