3 papers
cs.LG2025
Outlier detection in mixed-attribute data: a semi-supervised approach with fuzzy approximations and relative entropy
Baiyang Chen, Zhong Yuan, Zheng Liu +4
Outlier detection is a critical task in data mining, aimed at identifying objects that significantly deviate from the norm. Semi-supervised methods improve detection performance by…
cs.LG2025
Consistency-guided semi-supervised outlier detection in heterogeneous data using fuzzy rough sets
Baiyang Chen, Zhong Yuan, Dezhong Peng +2
Outlier detection aims to find samples that behave differently from the majority of the data. Semi-supervised detection methods can utilize the supervision of partial labels, thus…
cs.LG2025
Label-Informed Outlier Detection Based on Granule Density
Baiyang Chen, Zhong Yuan, Dezhong Peng +3
Outlier detection, crucial for identifying unusual patterns with significant implications across numerous applications, has drawn considerable research interest. Existing semi-supe…