A Novel Imbalanced Data Classification Approach Based on Logistic Regression and Fisher Discriminant
Joint Authors
Wang, Jing
Qi, Junyan
Cheng, Yanqiu
Shi, Baofeng
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-10
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
We introduce an imbalanced data classification approach based on logistic regression significant discriminant and Fisher discriminant.
First of all, a key indicators extraction model based on logistic regression significant discriminant and correlation analysis is derived to extract features for customer classification.
Secondly, on the basis of the linear weighted utilizing Fisher discriminant, a customer scoring model is established.
And then, a customer rating model where the customer number of all ratings follows normal distribution is constructed.
The performance of the proposed model and the classical SVM classification method are evaluated in terms of their ability to correctly classify consumers as default customer or nondefault customer.
Empirical results using the data of 2157 customers in financial engineering suggest that the proposed approach better performance than the SVM model in dealing with imbalanced data classification.
Moreover, our approach contributes to locating the qualified customers for the banks and the bond investors.
American Psychological Association (APA)
Shi, Baofeng& Wang, Jing& Qi, Junyan& Cheng, Yanqiu. 2015. A Novel Imbalanced Data Classification Approach Based on Logistic Regression and Fisher Discriminant. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1075140
Modern Language Association (MLA)
Shi, Baofeng…[et al.]. A Novel Imbalanced Data Classification Approach Based on Logistic Regression and Fisher Discriminant. Mathematical Problems in Engineering No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1075140
American Medical Association (AMA)
Shi, Baofeng& Wang, Jing& Qi, Junyan& Cheng, Yanqiu. A Novel Imbalanced Data Classification Approach Based on Logistic Regression and Fisher Discriminant. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1075140
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1075140