The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
SVM-RFE With MRMR Filter for Gene Selection
Open accessAbstract
We enhance the support vector machine recursive feature elimination (SVM-RFE) method for gene selection by incorporating a minimum-redundancy maximum-relevancy (MRMR) filter. The relevancy of a set of genes are measured by the mutual information among genes and class labels, and the redundancy is given by the mutual information among the genes. The method improved identification of cancer tissues from benign tissues on several benchmark datasets, as it takes into account the redundancy among the genes during their selection. The method selected a less number of genes compared to MRMR or SVM-RFE on most datasets. Gene ontology analyses revealed that the method selected genes that are relevant for distinguishing cancerous samples and have similar functional properties. The method provides a framework for combining filter methods and wrapper methods of gene selection, as illustrated with MRMR and SVM-RFE methods.
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Cited by
A survey on feature selection methods
Chandrashekar, G., & Sahin, F. (2014) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2013.11.024 · Cited by 5,189
A review of microarray datasets and applied feature selection methods
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Supervised, Unsupervised, and Semi-Supervised Feature Selection: A Review on Gene Selection
Ang, J. C., Mirzal, A., Haron, H., & Hamed, H. N. A. (2016) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2015.2478454 · Cited by 641
Feature selection and analysis on correlated gas sensor data with recursive feature elimination
Yan, K., & Zhang, D. (2015) · Sensors and Actuators B: Chemical · doi:10.1016/j.snb.2015.02.025 · Cited by 516
From explanations to feature selection: assessing SHAP values as feature selection mechanism
Marcilio, W. E., & Eler, D. M. (2020) · 2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) · doi:10.1109/sibgrapi51738.2020.00053 · Cited by 504
Metadata
- Authors
- Mundra, P. A., & Rajapakse, J. C.
- Venue
- IEEE Transactions on NanoBioscience
- Published
- 2010-03
- Volume
- 9
- Issue
- 1
- Pages
- 31-37
- ISSN
- 1536-1241 (ISSN-L)
- OpenAlex
- W2141826465
- Cited by
- 332
- References
- 36
- FWCI
- 2.88
- Type
- journal article
- Language
- en
- Open access
- green
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