The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Feature selection and analysis on correlated gas sensor data with recursive feature elimination
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Citations
Cites
A Tutorial on Support Vector Machines for Pattern Recognition
Burges, C. J. C. (1998) · Data Mining and Knowledge Discovery · doi:10.1023/a:1009715923555 · Cited by 16,429
Peng, H., Long, F., & Ding, C. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.159 · Cited by 10,544
Gene selection for cancer classification using support vector machines
Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002) · Machine Learning · doi:10.1023/a:1012487302797 · Cited by 9,954
An introduction to variable and feature selection
GuyonIsabelle, & ElisseeffAndré (2003) · Journal of Machine Learning Research · doi:10.5555/944919.944968 · Cited by 7,715
An Introduction to Variable and Feature Selection.
Guyon, I., & Elisseeff, A. (2003) · Cited by 6,576
A review of feature selection techniques in bioinformatics
Saeys, Y., Inza, I., & Larrañaga, P. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm344 · Cited by 5,244
Robust Feature Selection Using Ensemble Feature Selection Techniques
Saeys, Y., Abeel, T., & Van de Peer, Y. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-87481-2_21 · Cited by 663
Variable selection using svm based criteria
Rakotomamonjy, A. (2003) · Journal of Machine Learning Research · doi:10.5555/944919.944977 · Cited by 616
Stability of feature selection algorithms: a study on high-dimensional spaces
Kalousis, A., Prados, J., & Hilario, M. (2007) · Knowledge and Information Systems · doi:10.1007/s10115-006-0040-8 · Cited by 614
Multiple SVM-RFE for Gene Selection in Cancer Classification With Expression Data
Duan, K.-B., Rajapakse, J. C., Wang, H., & Azuaje, F. (2005) · IEEE Transactions on Nanobioscience · doi:10.1109/tnb.2005.853657 · Cited by 468
Cited by
A Review of Feature Selection and Its Methods
Venkatesh, B., & Anuradha, J. (2019) · Cybernetics and Information Technologies · doi:10.2478/cait-2019-0001 · Cited by 631
Stability of feature selection algorithm: A review
Khaire, U. M., & Dhanalakshmi, R. (2022) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2019.06.012 · Cited by 630
Gas Sensors Based on Chemi-Resistive Hybrid Functional Nanomaterials
Jian, Y., Hu, W., Zhao, Z., Cheng, P., Haick, H., Yao, M., & Wu, W. (2020) · Nano-Micro Letters · doi:10.1007/s40820-020-0407-5 · Cited by 429
Marín-Morales, J., Higuera-Trujillo, J. L., Greco, A., Guixeres, J., Llinares, C., Scilingo, E. P., Alcañiz, M., & Valenza, G. (2018) · Scientific Reports · doi:10.1038/s41598-018-32063-4 · Cited by 411
Data-centric Artificial Intelligence: A Survey
Zha, D., Bhat, Z. P., Lai, K.-H., Yang, F., Jiang, Z., Zhong, S., & Hu, X. (2025) · ACM Computing Surveys · doi:10.1145/3711118 · Cited by 334
Metadata
- Authors
- Yan, K., & Zhang, D.
- Venue
- Sensors and Actuators B: Chemical
- Publisher
- Elsevier BV
- Published
- 2015-06
- Volume
- 212
- Pages
- 353-363
- ISSN
- 0925-4005 (ISSN-L)
- OpenAlex
- W2020089616
- Cited by
- 516
- References
- 27
- FWCI
- 11.01
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yan, K., & Zhang, D. (2015). Feature selection and analysis on correlated gas sensor data with recursive feature elimination. Sensors and Actuators B: Chemical. https://doi.org/10.1016/j.snb.2015.02.025
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.
