The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Correlation feature selection based improved-Binary Particle Swarm Optimization for gene selection and cancer classification
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Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
Particle swarm optimization: An overview
Poli, R., Kennedy, J., & Blackwell, T. (2007) · Swarm Intelligence · doi:10.1007/s11721-007-0002-0 · Cited by 21,101
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
Golub, T. R., Slonim, D. K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J. P., Coller, H., Loh, M. L., Downing, J. R., Caligiuri, M. A., et al. (1999) · Science · doi:10.1126/science.286.5439.531 · Cited by 11,516
A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
Kohavi, R. (1995) · Zenodo · doi:10.5281/zenodo.19712698 · Cited by 10,909
Wrappers for feature subset selection
Kohavi, R., & John, G. H. (1997) · Artificial Intelligence · doi:10.1016/s0004-3702(97)00043-x · Cited by 8,947
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
A discrete binary version of the particle swarm algorithm
Kennedy, J., & Eberhart, R. C. (2002) · 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation · doi:10.1109/icsmc.1997.637339 · Cited by 4,767
Alon, U., Barkai, N., Notterman, D. A., Gish, K., Ybarra, S., Mack, D., & Levine, A. J. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.12.6745 · Cited by 4,167
Cited by
Particle Swarm Optimization: A Comprehensive Survey
Shami, T. M., El-Saleh, A. A., Alswaitti, M., Al-Tashi, Q., Summakieh, M. A., & Mirjalili, S. (2022) · IEEE Access · doi:10.1109/access.2022.3142859 · Cited by 1,584
A review of feature selection methods in medical applications
Remeseiro, B., & Bolon-Canedo, V. (2019) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2019.103375 · Cited by 804
Major Advances in Particle Swarm Optimization: Theory, Analysis, and Application
Houssein, E. H., Gad, A. G., Hussain, K., & Suganthan, P. N. (2021) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2021.100868 · Cited by 466
RetractedReview of swarm intelligence-based feature selection methods
Rostami, M., Berahmand, K., Nasiri, E., & Forouzandeh, S. (2021) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2021.104210 · Cited by 451
Feature selection using bare-bones particle swarm optimization with mutual information
Song, X.-F., Zhang, Y., Gong, D.-W., & Sun, X.-Y. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2020.107804 · Cited by 266
Metadata
- Authors
- Jain, I., Jain, V. K., & Jain, R.
- Venue
- Applied Soft Computing
- Publisher
- Elsevier BV
- Published
- 2018-01
- Volume
- 62
- Pages
- 203-215
- ISSN
- 1568-4946 (ISSN-L)
- OpenAlex
- W2763523016
- Cited by
- 423
- References
- 42
- FWCI
- 12.13
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Correlation feature selection based improved-Binary Particle Swarm Optimization for gene selection and cancer classification. https://app.cochat.ai/papers/10.1016/j.asoc.2017.09.038
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- Jain, I., Jain, V. K., & Jain, R. (2018). Correlation feature selection based improved-Binary Particle Swarm Optimization for gene selection and cancer classification. Applied Soft Computing. https://doi.org/10.1016/j.asoc.2017.09.038
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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.
