TY - JOUR
T1 - Integrated framework for profit-based feature selection and SVM classification in credit scoring
AU - Maldonado, Sebastián
AU - Bravo, Cristián
AU - López, Julio
AU - Pérez, Juan
PY - 2017/12/1
Y1 - 2017/12/1
N2 - . In this paper, we propose a profit-driven approach for classifier construction and simultaneous variable selection based on linear Support Vector Machines. The main goal is to incorporate business-related information such as the variable acquisition costs, the Types I and II error costs, and the profit generated by correctly classified instances, into the modeling process. Our proposal incorporates a group penalty function in the SVM formulation in order to penalize the variables simultaneously that belong to the same group, assuming that companies often acquire groups of related variables for a given cost rather than acquiring them individually. The proposed framework was studied in a credit scoring problem for a Chilean bank, and led to superior performance with respect to business-related goals.
AB - . In this paper, we propose a profit-driven approach for classifier construction and simultaneous variable selection based on linear Support Vector Machines. The main goal is to incorporate business-related information such as the variable acquisition costs, the Types I and II error costs, and the profit generated by correctly classified instances, into the modeling process. Our proposal incorporates a group penalty function in the SVM formulation in order to penalize the variables simultaneously that belong to the same group, assuming that companies often acquire groups of related variables for a given cost rather than acquiring them individually. The proposed framework was studied in a credit scoring problem for a Chilean bank, and led to superior performance with respect to business-related goals.
KW - Analytics
KW - Credit scoring
KW - Group penalty
KW - Profit measure
KW - Support Vector Machines
KW - Analytics
KW - Credit scoring
KW - Group penalty
KW - Profit measure
KW - Support Vector Machines
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85033556242&origin=inward
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U2 - 10.1016/j.dss.2017.10.007
DO - 10.1016/j.dss.2017.10.007
M3 - Article
VL - 104
SP - 113
EP - 121
JO - Decision Support Systems
JF - Decision Support Systems
SN - 0167-9236
ER -