1,290
Views
3
CrossRef citations to date
0
Altmetric
Theory and Methods

Feature Screening with Conditional Rank Utility for Big-Data Classification

& ORCID Icon
Pages 1385-1395 | Received 20 Jul 2022, Accepted 15 Mar 2023, Published online: 18 Apr 2023

References

  • Battey, H., Fan, J., Liu, H., Lu, J., and Zhu, Z. (2018), “Distributed Testing and Estimation Under Sparse High Dimensional Models,” The Annals of Statistics, 46, 1352–1382. DOI: 10.1214/17-AOS1587.
  • Cheng, G., Li, X., Lai, P., Song, F., and Yu, J. (2017), “Robust Rank Screening for Ultrahigh Dimensional Discriminant Analysis,” Statistics and Computing, 27, 535–545. DOI: 10.1007/s11222-016-9637-2.
  • Cui, H., Li, R., and Zhong, W. (2015), “Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis,” Journal of the American Statistical Association, 110, 630–641. DOI: 10.1080/01621459.2014.920256.
  • Dua, D., and Graff, C. (2019), “UCI Machine Learning Repository,” University of California, Irvine, School of Information and Computer Sciences. Available at http://archive.ics.uci.edu/ml.
  • Fan, J., and Fan, Y. (2008), “High Dimensional Classification Using Features Annealed Independence Rules,” Annals of Statistics, 36, 2605–2637. DOI: 10.1214/07-AOS504.
  • Fan, J., Guo, Y., and Wang, K. (2021), “Communication-Efficient Accurate Statistical Estimation,” Journal of the American Statistical Association. DOI: 10.1080/01621459.2021.1969238.
  • Fan, J., and Lv, J. (2008), “Sure Independence Screening for Ultrahigh Dimensional Feature Space,” Journal of the Royal Statistical Society, Series B, 70, 849–911. DOI: 10.1111/j.1467-9868.2008.00674.x.
  • Fan, J., and Ren, Y. (2006), “Statistical Analysis of DNA Microarray Data in Cancer Research,” Clinical Cancer Research, 12, 4469–4473. DOI: 10.1158/1078-0432.CCR-06-1033.
  • Fan, J., Samworth, R., and Wu, Y. (2009), “Ultrahigh Dimensional Feature Selection: Beyond the Linear Model,” Journal of Machine Learning Research, 10, 2013–2038.
  • Gao, Y., Liu, W., Wang, H., Wang, X., Yan, Y., and Zhang, R. (2021), “A Review of Distributed Statistical Inference,” Statistical Theory and Related Fields, 6, 89–99. DOI: 10.1080/24754269.2021.1974158.
  • Hoeffding, W. (1992), “A Class of Statistics with Asymptotically Normal Distribution,” in Breakthroughs in Statistics, eds. S. Kotz, and N. L. Johnson, pp. 308–334, New York: Springer.
  • Huang, C., and Huo, X. (2015), “A Distributed One-Step Estimator,” arXiv preprint arXiv:1511.01443.
  • Jochems, A., Deist, T. M., Van Soest, J., Eble, M., Bulens, P., Coucke, P., Dries, W., Lambin, P., and Dekker, A. (2016), “Distributed Learning: Developing a Predictive Model based on Data from Multiple Hospitals Without Data Leaving the Hospital–A Real Life Proof of Concept,” Radiotherapy and Oncology, 121, 459–467. DOI: 10.1016/j.radonc.2016.10.002.
  • Jordan, M. I., Lee, J. D., and Yang, Y. (2019), “Communication-Efficient Distributed Statistical Inference,” Journal of the American Statistical Association, 114, 668–681. DOI: 10.1080/01621459.2018.1429274.
  • Li, G., Peng, H., Zhang, J., and Zhu, L. (2012), “Robust Rank Correlation based Screening,” The Annals of Statistics, 40, 1846–1877. DOI: 10.1214/12-AOS1024.
  • Li, X., Cheng, G., Wang, L., Lai, P., and Song, F. (2017), “Ultrahigh Dimensional Feature Screening via Projection,” Computational Statistics & Data Analysis, 114, 88–104. DOI: 10.1016/j.csda.2017.04.006.
  • Li, X., Li, R., Xia, Z., and Xu, C. (2020), “Distributed Feature Screening via Componentwise Debiasing,” Journal of Machine Learning Research, 21, 1–32.
  • Mai, Q., and Zou, H. (2012), “The Kolmogorov Filter for Variable Screening in High-Dimensional Binary Classification,” Biometrika, 100, 229–234. DOI: 10.1093/biomet/ass062.
  • Mai, Q., and Zou, H. (2015), “The Fused Kolmogorov Filter: A Nonparametric Model-Free Screening Method,” The Annals of Statistics, 43, 1471–1497.
  • Pan, R., Wang, H., and Li, R. (2016), “Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening,” Journal of the American Statistical Association, 111, 169–179. DOI: 10.1080/01621459.2014.998760.
  • Wang, L., Li, X., Wang, X., and Lai, P. (2022), “Unified Mean-Variance Feature Screening for Ultrahigh-Dimensional Regression,” Computational Statistics, 37, 1887–1918. DOI: 10.1007/s00180-021-01184-2.
  • Wu, Y., and Yin, G. (2015), “Conditional Quantile Screening in Ultrahigh-Dimensional Heterogeneous Data,” Biometrika, 102, 65–76. DOI: 10.1093/biomet/asu068.
  • Xie, J., Lin, Y., Yan, X., and Tang, N. (2020), “Category-Adaptive Variable Screening for Ultra-High Dimensional Heterogeneous Categorical Data,” Journal of the American Statistical Association, 115, 747–760. DOI: 10.1080/01621459.2019.1573734.
  • Yan, X., Tang, N., and Zhao, X. (2017), “The Spearman Rank Correlation Screening for Ultrahigh Dimensional Censored Data,” arXiv preprint arXiv:1702.02708.
  • Zhang, Y., Duchi, J. C., and Wainwright, M. (2012), “Comunication-Efficient Algorithms for Statistical Optimization,” Journal of Machine Learning Research, 14, 3321–3363.
  • Zhong, W. (2014), “Robust Sure Independence Screening for Ultrahigh Dimensional Non-Normal Data,” Acta Mathematica Sinica, English Series, 30, 1885–1896. DOI: 10.1007/s10114-014-3694-2.
  • Zhu, L.-P., Li, L., Li, R., and Zhu, L.-X. (2011), “Model-Free Feature Screening for Ultrahigh-Dimensional Data,” Journal of the American Statistical Association, 106, 1464–1475. DOI: 10.1198/jasa.2011.tm10563.
  • Zhu, X., Pan, R., Wu, S., and Wang, H. (2021), “Feature Screening for Massive Data Analysis by Subsampling,” Journal of Business & Economic Statistics, 40, 1892–1903. DOI: 10.1080/07350015.2021.1990771.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.