Advances in Operations Research / 2019 / Article / Tab 9

Review Article

Credit Scoring: A Review on Support Vector Machines and Metaheuristic Approaches

Table 9

Results categorized with data splitting methods.

Data Split Authors G A

k-fold cvDong et al. [66] 72.90 -
Uthayakumar et al. [69]- 86.37
Zhang et al. [38]79.8889.45
Xu et al. [40] -89.28
Han et al. [50] 75.00 -
Zhang et al. [78] 77.7689.33
Yao [39] 76.60 87.52
Chen and Li [43] 76.70 86.52
Jadhav et al. [54]82.8090.75
Wang et al. [55]78.53 86.96
Huang and Wu [83] - 87.54
Oreski and Oreski [86]78.90 -
Wang et al. [88] -88.90
Zhou et al. [42] 77.10 86.96
Yu et al. [44]78.4690.63
Hsu et al. [53]84.0092.75
Huang et al. [35] 77.92 86.90
mean 78.20 88.56
standard deviation 2.93 1.92

holdout Baesens et al. [8] 74.3089.10
Cai et al. [63]80.00 -
Boughaci and Alkhawaldeh [18] 69.90 80.70
Harris [29]77.10 -
Zhou et al. [56]78.13 -
Ghodselahi [57]81.42 -
Martens et al. [36] - 85.10
Martens et al. [67]80.80 -
Aliehyaei and Khan [71] 70.70 84.30
Garsva and Danenas [51]81.3087.40
mean 77.07 85.32
standard deviation 4.47 3.20

rep k-fold Lessmann et al. [11] 75.30 86.00
Xia et al. [59]78.32 86.29
Krishnaveni et al. [90]80.4093.50
mean 78.01 88.60
standard deviation 2.56 4.25

rep holdout Ong et al. [61] 77.3488.27
Huang et al. [64]79.4989.17
Lacerda et al. [75] - 86.05
mean 78.42 87.83
standard deviation 1.52 1.61

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