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Wireless Communications and Mobile Computing
Volume 2017, Article ID 6817627, 13 pages
https://doi.org/10.1155/2017/6817627
Research Article

A Variable Impacts Measurement in Random Forest for Mobile Cloud Computing

1Department of IT Engineering, Sookmyung Women’s University, Cheongpa-ro 47-gil 100, Yongsan-gu, Seoul 04310, Republic of Korea
2Big Data Using Research Center, Sookmyung Women’s University, Cheongpa-ro 47-gil 100, Yongsan-gu, Seoul 04310, Republic of Korea

Correspondence should be addressed to Young-Ho Park; rk.ca.ms@kraphy

Received 13 April 2017; Accepted 13 June 2017; Published 7 September 2017

Academic Editor: B. B. Gupta

Copyright © 2017 Jae-Hee Hur et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. K. J. Archer and R. V. Kimes, “Empirical characterization of random forest variable importance measures,” Computational Statistics & Data Analysis, vol. 52, no. 4, pp. 2249–2260, 2008. View at Publisher · View at Google Scholar · View at MathSciNet
  2. L. Breiman, “Random forests,” Machine Learning, vol. 45, no. 1, pp. 5–32, 2001. View at Publisher · View at Google Scholar · View at Scopus
  3. S. Cohen, E. Ruppin, and G. Dror, “Feature selection based on the Shapley value,” In Other Words, vol. 1, 2005. View at Google Scholar
  4. O. Okun and H. Priisalu, “Random forest for gene expression based cancer classification: overlooked issues,” in Pattern Recognition and Image Analysis, pp. 483–490, Springer, 2007. View at Publisher · View at Google Scholar
  5. A. Statnikov, L. Wang, and C. F. Aliferis, “A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification,” BMC Bioinformatics, vol. 9, article 319, pp. 1–10, 2008. View at Publisher · View at Google Scholar · View at Scopus
  6. R. Díaz-Uriarte and S. Alvarez de Andrés, “Gene selection and classification of microarray data using random forest,” BMC Bioinformatics, vol. 7, no. 1, article 3, 2006. View at Publisher · View at Google Scholar · View at Scopus
  7. B. Wu, T. Abbott, D. Fishman et al., “Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data,” Bioinformatics, vol. 19, no. 13, pp. 1636–1643, 2003. View at Publisher · View at Google Scholar · View at Scopus
  8. A. Hapfelmeier, T. Hothorn, K. Ulm, and C. Strobl, “A new variable importance measure for random forests with missing data,” Statistics and Computing, vol. 24, no. 1, pp. 21–34, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  9. B. Gregorutti, B. Michel, and P. Saint-Pierre, “Correlation and variable importance in random forests,” Statistics and Computing, vol. 27, no. 3, pp. 659–678, 2017. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  10. H. Wang, F. Yang, and Z. Luo, “An experimental study of the intrinsic stability of random forest variable importance measures,” BMC Bioinformatics, vol. 17, no. 1, 2016. View at Publisher · View at Google Scholar · View at Scopus
  11. D. Harrison and D. L. Rubinfeld, “Hedonic prices and the demand for clean air,” Journal of Environmental Economics and Management, vol. 5, pp. 81–102, 1978. View at Publisher · View at Google Scholar
  12. C. Strobl, A.-L. Boulesteix, T. Kneib, T. Augustin, and A. Zeileis, “Conditional variable importance for random forests,” BMC Bioinformatics, vol. 9, no. 1, article 307, 2008. View at Publisher · View at Google Scholar · View at Scopus
  13. S. Lipovetsky and M. Conklin, “Analysis of regression in game theory approach,” Applied Stochastic Models in Business and Industry, vol. 17, no. 4, pp. 319–330, 2001. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  14. M. Bowling and V. Manuela, An Analysis of Stochastic Game Theory for Multiagent Reinforcement Learning, Carnegie-Mellon Univ Pittsburgh Pa School of Computer Science, 2000.
  15. L. S. Shapley, “A value for n-person games,” in Contributions to the Theory of Games, H. Kuhn and A. W. Tucker, Eds., vol. 2 of Annals of Mathematics Studies, pp. 307–317, Princeton University Press, Princeton, NJ, USA, 1953. View at Google Scholar · View at MathSciNet
  16. S. RColorBrewer, A. Liaw, M. Wiener, and M. A. Liaw, “Package ‘randomForest’,” 2015.