journal article·2024Open access

Data-Driven Decision-Making for Bank Target Marketing Using Supervised Learning Classifiers on Imbalanced Big Data

Fahim Nasir, Abdulghani Ali Ahmed, Mehmet Sabir Kiraz, Iryna Yevseyeva, Mubarak Saif

Computers, Materials & Continua· Volume 81· Issue 1

Abstract

Integrating machine learning and data mining is crucial for processing big data and extracting valuable insights to enhance decision-making. However, imbalanced target variables within big data present technical challenges th... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Imbalanced Data Classification Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (28)

Show source-provided references
1. Impact of big data analytics on banking: A case study
2. Supervised machine learning: A review of classification techniques
3. Knowledge discovery: Methods from data mining and machine learning10.1016/j.ssresearch.2022.102817 ↗
4. Unbalanced credit card fraud detection data: A machine learning-oriented comparative study of balancing techniques10.1016/j.procs.2023.01.231 ↗
5. Predictive analytics in business analytics: Decision tree
6. Predictive analytics and machine learning in direct marketing for anticipating bank term deposit subscriptions
7. Comprehensive survey on big data privacy protection10.1109/ACCESS.2019.2962368 ↗
8. Comparative evaluation of imbalanced data management techniques for solving classification problems on imbalanced datasets10.19139/soic-2310-5070-1890 ↗
9. Comparing the performance of AdaBoost, XGBoost, and logistic regression for imbalanced data10.13189/ms.2021.090320 ↗
10. A comparison of undersampling, oversampling, and SMOTE methods for dealing with imbalanced classification in educational data mining10.3390/info14010054 ↗
11. Imbalanced data preprocessing techniques for machine learning: A systematic mapping study10.1007/s10115-022-01772-8 ↗
12. Moro · UCI Machine Learning Repository · 2014
13. Efficient hybrid oversampling and intelligent undersampling for imbalanced big data classification
14. Artificial intelligence techniques in financial trading: A systematic literature review
15. A comparative study of business intelligence and artificial intelligence with big data analytics
16. S. Dridi, “Supervised learning–A systematic literature review,” Dec. 2021. doi: 10.31219/osf.io/tysr4.10.31219/osf.io/tysr4 ↗
17. Hybrid approaches to optimization and machine learning methods: A systematic literature review10.1007/s10994-023-06467-x ↗
18. Customer behaviour-based fraud detection of credit card using a random forest algorithm
19. Research paper classification using supervised machine learning techniques
20. Supervised machine learning algorithms: Classification and comparison10.14445/22312803/IJCTT-V48P126 ↗
21. A state of art techniques on machine learning algorithms: A perspective of supervised learning approaches in data classification
22. Using machine learning algorithms to solve data classification problems using multi-attribute dataset10.1051/bioconf/20248402001 ↗
23. Predicting money laundering using machine learning and artificial neural networks algorithms in banks10.1080/19361610.2022.2114744 ↗
24. Big data project-bank marketing campaign
25. A data driven approach to predict the success of bank telemarketing10.1016/j.dss.2014.03.001 ↗
26. K. Wlodarczyk and K. S. Ikani, “Data analysis of a Portuguese marketing campaign using bank marketing dataset,” 2020, Accessed: Aug. 10, 2023. [Online]. Available: https://www.researchgate.net/publication/339988208
27. How to improve the success of bank telemarketing? Prediction and interpretability analysis based on machine learning10.1016/j.cie.2022.108874 ↗
28. Machine learning models and algorithms for big data classification