Credit Card Fraud Detection using Data Pre-processing on Imbalanced Data - both Oversampling and Undersampling-Reference-Cited by-同舟云学术

Credit Card Fraud Detection using Data Pre-processing on Imbalanced Data - both Oversampling and Undersampling

Published:2020-01-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Conference on Computing Advancements
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Author:

Ahammad Jalal¹,Hossain Nazia¹,Alam Mohammad Shafiul²

Affiliation:

1. Stamford University Bangladesh, Dhaka, Bangladesh

2. Ahsanullah University of Science and Technology, Dhaka, Bangladesh

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3377049.3377113

Reference17 articles.

1. [n.d.]. 24 Best Ecommerce Retail Datasets for Machine Learning | Lionbridge AI. https://lionbridge.ai/datasets/24-best-ecommerce- retail- datasets- for- machine-learning/ [n.d.]. 24 Best Ecommerce Retail Datasets for Machine Learning | Lionbridge AI. https://lionbridge.ai/datasets/24-best-ecommerce- retail- datasets- for- machine-learning/

2. [n.d.]. Decision Trees-A simple way to visualize a decision. https://medium.com/greyatom/decision-trees-a-simple-way-to-visualize-a-decision-dc506a403aeb [n.d.]. Decision Trees-A simple way to visualize a decision. https://medium.com/greyatom/decision-trees-a-simple-way-to-visualize-a-decision-dc506a403aeb

3. Workflow mining: Discovering process models from event logs;Der Aalst Wil Van;Issue 9. https://doi.org/10.1109/TKDE.,2004

4. Astha Agrawal Herna L Viktor and Eric Paquet. [n.d.]. SCUT: Multi-Class Imbalanced Data Classification using SMOTE and Cluster-based Undersampling. Astha Agrawal Herna L Viktor and Eric Paquet. [n.d.]. SCUT: Multi-Class Imbalanced Data Classification using SMOTE and Cluster-based Undersampling.

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