The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A hybrid method for imputation of missing values using optimized fuzzy c-means with support vector regression and a genetic algorithm
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Citations
Cites
Missing data: our view of the state of the art
Schafer, J. L., & Graham, J. W. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.2.147 · Cited by 11,638
Cited by
A survey on missing data in machine learning
Emmanuel, T., Maupong, T., Mpoeleng, D., Semong, T., Mphago, B., & Tabona, O. (2021) · Journal of Big Data · doi:10.1186/s40537-021-00516-9 · Cited by 1,067
Missing value imputation: a review and analysis of the literature (2006–2017)
Lin, W.-C., & Tsai, C.-F. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-019-09709-4 · Cited by 612
Zhu, J., Ge, Z., Song, Z., & Gao, F. (2018) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2018.09.003 · Cited by 308
Machine Learning-Enabled Internet of Things (IoT): Data, Applications, and Industry Perspective
Bzai, J., Alam, F., Dhafer, A., Bojović, M., Altowaijri, S. M., Niazi, I. K., & Mehmood, R. (2022) · Electronics · doi:10.3390/electronics11172676 · Cited by 110
How to Address the Data Quality Issues in Regression Models: A Guided Process for Data Cleaning
Corrales, D., Corrales, J., & Ledezma, A. (2018) · Symmetry · doi:10.3390/sym10040099 · Cited by 58
Metadata
- Authors
- Aydilek, I. B., & Arslan, A.
- Venue
- Information Sciences
- Publisher
- Elsevier BV
- Published
- 2013-06
- Volume
- 233
- Pages
- 25-35
- ISSN
- 0020-0255 (ISSN-L)
- OpenAlex
- W2039015671
- Cited by
- 322
- References
- 1
- FWCI
- 19.14
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Aydilek, I. B., & Arslan, A. (2013). A hybrid method for imputation of missing values using optimized fuzzy c-means with support vector regression and a genetic algorithm. Information Sciences. https://doi.org/10.1016/j.ins.2013.01.021
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
