A Framework of Rebalancing Imbalanced Healthcare Data for Rare Events’ Classification: A Case of Look-Alike Sound-Alike Mix-Up Incident Detection

Table 2

Parameter settings for algorithms

(a)

A.1 Random oversampling + LR
Settings for ratio1
ratio1	1.5	2.0	2.5	3.0	3.5	4.0	4.5	5.0
A.2 Random undersampling + LR
Settings for ratio2
ratio2	1/1.5	1/2.0	1/2.5	1/3.0	1/3.5	1/4.0	1/4.5	1/5.0

(b)

A.3 SMOTE + LR
Settings for α and γ
α	400	300	200	100	200	100	100
γ	100	100	100	100	200	200	300

(c)

A.4 Cost-sensitive learning + LR
Settings for threshold
threshold	0.5	0.25	0	−0.25	−0.5	−1	−1.5	−2