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2021 | OriginalPaper | Chapter

Modified Decision Tree Learning for Cost-Sensitive Credit Card Fraud Detection Model

Authors : Sudhansu R. Lenka, Rabindra K. Barik, Sudhashu S. Patra, Vinay P. Singh

Published in: Advances in Communication and Computational Technology

Publisher: Springer Nature Singapore

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Abstract

Credit card fraudulent transactions are cost-sensitive in nature, where the cost differs in each misclassification transaction. Generally, the classification methods do not work on the cost factor. It considers a constant cost factor for each misclassification. In this paper, it proposes a modified instance-based cost-sensitive decision tree algorithm which reflects on different cost factor for each misclassified transactions. In the proposed algorithm, it implements different instance-based costs into the cost-based impurity measure as well as cost-based pruning approach. Experimentally, it shows that the proposed algorithm performs better in terms of cost savings as compared against classical decision tree algorithms. Additionally, it observes that the smaller trees are generated in minimum computational time.

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Metadata
Title
Modified Decision Tree Learning for Cost-Sensitive Credit Card Fraud Detection Model
Authors
Sudhansu R. Lenka
Rabindra K. Barik
Sudhashu S. Patra
Vinay P. Singh
Copyright Year
2021
Publisher
Springer Nature Singapore
Book
Advances in Communication and Computational Technology

Print ISBN: 978-981-15-5340-0

Electronic ISBN: 978-981-15-5341-7

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-5341-7_113