Feature selection in mixed data: A method using a novel fuzzy rough set-based information entropy

By Xiao Zhang, Changlin Mei, De-gang Chen, Jinhai Li. Pattern Recognition, 2016

336 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Information Systems

View Paper: https://www.semanticscholar.org/paper/71975e0c2424865692fc230787ea0be7038496de

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Yan Song
2. Yunqiang Liu
3. Zhiyi Meng
4. Jialing Zhu
5. Eldon Y. Li
6. H. Koster

Citations in the corpus

• Environmental regulation, green technological innovation, and eco-efficiency: The case of Yangtze river economic belt in China (2020, methodology): “…fuzzy rough sets based on fuzzy relations are used to measure the similarity between the objects and remove the redundant and irrelevant attributes without significantly decreasing the prediction accuracy of the classifier that has been built only from the selected features (Zhang et al., 2016).”