Credit Card Fraud Detection Algorithm using Decision Treesbased Random Forest Classifier
Main Article Content
Abstract
In this paper we mainly focus on credit card fraud detection in real world. Here the credit card fraud
detection is based on fraudulent transactions. Generally, credit card fraud activities can happen in both
online and offline. But in today's world online fraud transaction activities are increasing day by day.
So,to find the online fraud transactions various methods have been used in existing system. In
proposed system we use random forest algorithm(RFA) for finding the fraudulent transactions and the
accuracy of those transactions. This algorithm is based on supervised learning algorithm where it uses
decision trees for classification of the dataset. After classification of dataset a confusion matrix is
obtained. The performance of RFA is evaluated based on the confusion matrix.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.