Dynamic interactive weighted feature selection using fuzzy interaction information
XA Ma, H Xu, Y Liu - Applied Intelligence, 2025 - Springer
Traditional information theory-based feature selection methods are designed for discrete
features, which require additional discretization steps when working with continuous …
features, which require additional discretization steps when working with continuous …
A composite entropy-based uncertainty measure guided attribute reduction for imbalanced mixed-type data
W Shu, S Li, W Qian - Journal of Intelligent & Fuzzy Systems, 2024 - content.iospress.com
In real-world scenarios, datasets generally exhibit containing mixed-type of attributes and
imbalanced classes distribution, and the minority classes in the data are the primary …
imbalanced classes distribution, and the minority classes in the data are the primary …
Attribute reductions based on δ-fusion condition entropy and harmonic similarity degree in interval-valued decision systems
X Liu, B Chen - Journal of Intelligent & Fuzzy Systems, 2024 - content.iospress.com
This paper defines an improved similarity degree based on inclusion degree as well as
advanced information system based on interval coverage and credibility, and thus an …
advanced information system based on interval coverage and credibility, and thus an …
A novel attribute reduction approach using coverage-credibility-based rough decision entropy for interval-valued data
X Liu, X Zhang, J Chen, B Chen - Journal of Intelligent & Fuzzy … - content.iospress.com
Attribute reduction is an important method in data analysis and machine learning, and it
usually relies on algebraic and informational measures. However, few existing informational …
usually relies on algebraic and informational measures. However, few existing informational …