Cite
Semi-supervised feature selection for partially labeled mixed-type data based on multi-criteria measure approach.
MLA
Shu, Wenhao, et al. “Semi-Supervised Feature Selection for Partially Labeled Mixed-Type Data Based on Multi-Criteria Measure Approach.” International Journal of Approximate Reasoning, vol. 153, Feb. 2023, pp. 258–79. EBSCOhost, https://doi.org/10.1016/j.ijar.2022.11.020.
APA
Shu, W., Yu, J., Yan, Z., & Qian, W. (2023). Semi-supervised feature selection for partially labeled mixed-type data based on multi-criteria measure approach. International Journal of Approximate Reasoning, 153, 258–279. https://doi.org/10.1016/j.ijar.2022.11.020
Chicago
Shu, Wenhao, Jianhui Yu, Zhenchao Yan, and Wenbin Qian. 2023. “Semi-Supervised Feature Selection for Partially Labeled Mixed-Type Data Based on Multi-Criteria Measure Approach.” International Journal of Approximate Reasoning 153 (February): 258–79. doi:10.1016/j.ijar.2022.11.020.