A Hybrid Credit Scoring Model Based on Genetic Programming and Support Vector Machines

2008 ◽  
Author(s):  
Defu Zhang ◽  
Mhand Hifi ◽  
Qingshan Chen ◽  
Weiguo Ye
Keyword(s):  
Support Vector Machines ◽  
Genetic Programming ◽  
Credit Scoring ◽  
Support Vector ◽  
Scoring Model ◽  
Model Based ◽  
Vector Machines ◽  
Credit Scoring Model

Boosted Decision Trees for Credit Scoring

2022 ◽  
pp. 270-292
Author(s):  
Luca Di Persio ◽  
Alberto Borelli
Keyword(s):  
Support Vector Machines ◽  
Decision Trees ◽  
Prediction Accuracy ◽  
Credit Scoring ◽  
Support Vector ◽  
Scoring Model ◽  
Vector Machines ◽  
Boosted Decision Trees ◽  
The One ◽  
Credit Scoring Model

The chapter developed a tree-based method for credit scoring. It is useful because it helps lenders decide whether to grant or reject credit to their applicants. In particular, it proposes a credit scoring model based on boosted decision trees which is a technique consisting of an ensemble of several decision trees to form a single classifier. The analysis used three different publicly available datasets, and then the prediction accuracy of boosted decision trees is compared with the one of support vector machines method.

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