relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1942/
title: A Novel Credit Scoring Prediction Model based on Feature Selection Approach and Parallel Random Forest
creator: Ha, Van Sang
creator: Nguyen, Ha Nam
creator: Nguyen, Duc Nhan
subject: Information Technology (IT)
description: Background/Objectives: This article presents a method of feature selection to improve the accuracy and the computation speed of credit scoring models. Methods/Analysis: In this paper, we proposed a credit scoring model based on parallel Random Forest classifier and feature selection method to evaluate the credit risks of applicants. By integration of Random Forest into feature selection process, the importance of features can be accurately evaluated to remove irrelevant and redundant features. Findings: In this research, an algorithm to  ...
date: 2016-05
type: Article
type: PeerReviewed
identifier:   Ha, Van Sang and Nguyen, Ha Nam and Nguyen, Duc Nhan  (2016) A Novel Credit Scoring Prediction Model based on Feature Selection Approach and Parallel Random Forest.  Indian Journal of Science and Technology, 9  (20).