Semi-Supervised Outlier Detection for Mixed Data: A Fuzzy and Entropy-Based Approach
Published:Dec 22, 2025 02:41
•1 min read
•ArXiv
Analysis
This research paper explores a semi-supervised approach to outlier detection, a critical area within data analysis. The use of fuzzy approximations and relative entropy is a novel combination likely aiming to improve detection accuracy, particularly in complex datasets.
Key Takeaways
Reference
“The paper originates from ArXiv, suggesting it's a pre-print of a scientific research.”