Enhancing supply chain security with automated machine learning
By Haibo Wang, Lutfu S. Sua, Bahram Alidaee
Rating
878
Battle Count: 81
Relevance
5/10
While focused on supply chain management, the ML techniques and fraud detection aspects could be adapted to financial markets and trading
Implementation Complexity
7/10
Implementing an automated ML framework requires significant expertise, but the individual ML models used are relatively standard
Reproducibility
3/5
The paper provides some details on the methodology and datasets used, but full code and data are not explicitly made available
About this paper
Methodology: Automated Machine Learning. Problem types: Classification, Anomaly Detection, Time Series Forecasting.
The interactive Everscope explorer (charts, battles, favorites) loads below.