all AI news
Utilizing the LightGBM Algorithm for Operator User Credit Assessment Research
March 22, 2024, 4:42 a.m. | Shaojie Li, Xinqi Dong, Danqing Ma, Bo Dang, Hengyi Zang, Yulu Gong
cs.LG updates on arXiv.org arxiv.org
Abstract: Mobile Internet user credit assessment is an important way for communication operators to establish decisions and formulate measures, and it is also a guarantee for operators to obtain expected benefits. However, credit evaluation methods have long been monopolized by financial industries such as banks and credit. As supporters and providers of platform network technology and network resources, communication operators are also builders and maintainers of communication networks. Internet data improves the user's credit evaluation strategy. …
abstract algorithm arxiv assessment banks benefits communication credit cs.ai cs.lg decisions evaluation financial however industries internet lightgbm mobile operators q-fin.st research type
More from arxiv.org / cs.LG updates on arXiv.org
The Perception-Robustness Tradeoff in Deterministic Image Restoration
2 days, 22 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Founding AI Engineer, Agents
@ Occam AI | New York
AI Engineer Intern, Agents
@ Occam AI | US
AI Research Scientist
@ Vara | Berlin, Germany and Remote
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Machine Learning Engineer
@ Apple | Sunnyvale, California, United States