1. Chen, C., Liaw, A., & Breiman, L. (2004). Using Random Forest to learn imbalanced data. Berkeley: Department of Statistics, University of California. 12.
2. Colla, V., Matarese, N., & Nastasi, G. (2011). Prediction of under pickling defects on steel strip surface. International Journal of Soft Computing and Software Engineering, 1(1), 9–17. doi:
10.7321/jscse.v1.n1.2
.
3. de Beer, P. G., & Craig, K. J. (2008). Continuous cast width control using a data mining approach. Ironmaking & Steelmaking, 35(3), 213–220. doi:
10.1179/030192307X233052
.
4. Furtmueller, C., del Re, L., Bramerdorfer, H., & Moerwald, K. (2005). Periodic disturbance suppression in a steel plant with unstable internal feedback and delay. In Proceedings of 5th international conference on technology and automation, ICTA (vol. 5, pp. 1–6).
5. Galili, T. (2015). dendextend: an R package for visualizing, adjusting, and comparing trees of hierarchical clustering. Bioinformatics (Oxford, England), 31(22), 3718–3720. doi:
10.1093/bioinformatics/btv428
.