A hybrid feature selection method for credit scoring

Van-Sang Ha; Nam Nguyen Ha; Hien Nguyen Thi Bao

doi:10.60692/gk2re-g9w03

ScienceGate Book Chapters

JOURNAL ARTICLE

A hybrid feature selection method for credit scoring

Van-Sang Ha Nam Nguyen Ha Hien Nguyen Thi Bao

Year: 2017 Journal: Greater South Information System

DOI: 10.60692/gk2re-g9w03

Get Full-Text PDF Get Analytical Report

Abstract

Reliable credit scoring models played a very important role of retail banks to evaluate credit applications and it has been widely studied. The main objective of this paper is to build a hybrid credit scoring model using feature selection approach. In this study, we constructed a credit scoring mode

Keywords:

Feature selection Selection (genetic algorithm) Feature (linguistics) Credit risk Mode (computer interface) Credit score

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.66

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Financial Distress and Bankruptcy Prediction

Social Sciences → Business, Management and Accounting → Accounting

Imbalanced Data Classification Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Credit Risk and Financial Regulations

Social Sciences → Economics, Econometrics and Finance → Finance

A hybrid feature selection method for credit scoring

Abstract

Metrics

Topics

Related Documents

A hybrid feature selection method for credit scoring

A hybrid feature selection method for credit scoring

A hybrid model with novel feature selection method and enhanced voting method for credit scoring

Enhancing Credit Scoring: A Hybrid Feature Selection Algorithm for Loan Approval

Business-Oriented Feature Selection for Hybrid Classification Model of Credit Scoring