Combination of feature selection approaches with SVM in credit scoring
An effective classificatory model in credit scoring will objectively help managers who rely on intuitive experience. This study proposes four approaches using the SVM (support vector machine) classifier for feature selection that retain sufficient information for classification…
- from
- Credit Modeling
- added
- 2026-10-10
- likes
- 0
similar
-
A multi-objective approach for profit-driven feature selection in credit scoring sciencedirect.com
In credit scoring, feature selection aims at removing irrelevant data to improve the performance and interpretability of the scorecard. Standard techniques treat feature selection as a single-objective task and rely on statistical criteria such as correlation. Recent studies…
-
Data mining feature selection for credit scoring models link.springer.com
The features used may have an important effect on the performance of credit scoring models. The process of choosing the best set of features for credit scoring models is usually unsystematic and dominated by somewhat arbitrary trial. This paper presents an empirical study of…
-
Classification methods applied to credit scoring: Systematic review and overall comparison sciencedirect.com
The need for controlling and effectively managing credit risk has led financial institutions to excel in improving techniques designed for this purpose, resulting in the development of various quantitative models by financial institutions and consulting companies. Hence, the…
-
Credit scoring using the clustered support vector machine sciencedirect.com
Introduces the use of the clustered support vector machine (CSVM) for credit scorecard development. This recently designed algorithm addresses some of the limitations associated with traditional nonlinear support vector machine (SVM) based methods for classification…
-
A comparative study on base classifiers in ensemble methods for credit scoring sciencedirect.com
In the last years, the application of artificial intelligence methods on credit risk assessment has meant an improvement over classic methods. Recent works show that ensembles of classifiers achieve the better results for this kind of tasks.
-
Credit Risk Assessment Using Statistical and Machine Learning: Basic Methodology and Risk Modeling Applications link.springer.com
An important ingredient to accomplish the goal of a more efficient use of resources through risk modeling is to find accurate predictors of individual risk in the credit portfolios of institutions. In this context the authors make a comparative analysis of different statistical…
Credit Modeling › Feature Selection: “An effective classificatory model in credit scoring will objectively help managers who rely on intuitive experience. This study proposes four approaches using the SVM (support vector machine) classifier for feature selection that retain sufficient information for classification…”