An attribute-weighted isometric embedding method for categorical encoding on mixed data-Reference-Cited by-同舟云学术

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An attribute-weighted isometric embedding method for categorical encoding on mixed data

Published:2023-08-24 Issue:22 Volume:53 Page:26472-26496
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Liang Zupeng,Ji Shengfen,Li Qiude^ORCID,Hu Sigui,Yu Yang

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guizhou Province

Sciencce and technology Foundation of Guizhou Provincial Health Commission

Ph.D. Research Startup Foundation of Guizhou Medical University

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-023-04899-5.pdf

Reference48 articles.

1. Ramírez-Gallego S, Krawczyk B, García S, Wozniak M, Herrera F (2017) A survey on data preprocessing for data stream mining: Current status and future directions. Neurocomputing 239:39–57. https://doi.org/10.1016/j.neucom.2017.01.078

2. García S, Luengo J, Herrera F (2015) Data preprocessing in data mining. Intell Syst Refer Libr. https://doi.org/10.1007/978-3-319-10247-4

3. Zhang Y, Cheung YM (2022) A new distance metric exploiting heterogeneous interattribute relationship for ordinal-and-nominal-attribute data clustering. IEEE Trans Cybern 52:758–771. https://doi.org/10.1109/TCYB.2020.2983073

4. Mousavi E, Sehhati M (2023) A generalized multi-aspect distance metric for mixed-type data clustering. Pattern Recognit 138:109353. https://doi.org/10.1016/j.patcog.2023.109353

5. Li Q, Xiong Q, Ji S, Yu Y, Wu C, Yi H (2021) A method for mixed data classification base on RBF-ELM network. Neurocomputing 431:7–22. https://doi.org/10.1016/j.neucom.2020.12.032

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