Determination efficient classification algorithm for credit card owners : comparative study

Author

Aziz, Raghad A.

Source

Engineering and Technology Journal

Issue

Vol. 39, Issue 1B (31 Jan. 2021), pp.21-29, 9 p.

Publisher

University of Technology

Publication Date

2021-01-31

Country of Publication

Iraq

No. of Pages

9

Main Subjects

Electronic engineering

Topics

Abstract EN

Today in the business world, significant loss can happen when the borrowers ignore paying their loans.

Convenient credit-risk management represents a necessity for lending institutions.

In most times, some persons prefer to late their monthly payments, otherwise, they may face difficulties in the loan payment process to the financial institution.

Mainly, most fiscal organizations are considered managed and refined client classification systems, scanning a valid client from invalid ones.

This paper produces the data mining idea, specifically the classification technique of data mining and builds a system of data mining process structure.

The credit scoring problem will be applied using the Taiwan bank dataset.

Besides that, three classification methods are adopted, Naïve Bayesian, Decision Tree (C5.0), and Artificial Neural Network.

These classifiers are implemented in the WEKA machine learning application.

The results show that the C5.0 algorithm is the best among them, it achieves 0.93 accuracy rates, 0.94 detection rates, 0.96 precision rates, and 0.95 F-Measure which is higher than Naïve Bayesian and Artificial Neural Network; also, the False Positive Rate in C5.0 algorithm achieves 0.1 which is less than Artificial Neural Network and Naïve Bayesian.

American Psychological Association (APA)

Aziz, Raghad A.. 2021. Determination efficient classification algorithm for credit card owners : comparative study. Engineering and Technology Journal،Vol. 39, no. 1B, pp.21-29.
https://search.emarefa.net/detail/BIM-1282612

Modern Language Association (MLA)

Aziz, Raghad A.. Determination efficient classification algorithm for credit card owners : comparative study. Engineering and Technology Journal Vol. 39, no. 1B (2021), pp.21-29.
https://search.emarefa.net/detail/BIM-1282612

American Medical Association (AMA)

Aziz, Raghad A.. Determination efficient classification algorithm for credit card owners : comparative study. Engineering and Technology Journal. 2021. Vol. 39, no. 1B, pp.21-29.
https://search.emarefa.net/detail/BIM-1282612

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 29

Record ID

BIM-1282612