IDEAS home Printed from https://ideas.repec.org/r/inm/oropre/v13y1965i3p444-452.html
   My bibliography  Save this item

Linear and Nonlinear Separation of Patterns by Linear Programming

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Z. R. Gabidullina, 2013. "A Linear Separability Criterion for Sets of Euclidean Space," Journal of Optimization Theory and Applications, Springer, vol. 158(1), pages 145-171, July.
  2. Ya-Ju Fan & Wanpracha Chaovalitwongse, 2010. "Optimizing feature selection to improve medical diagnosis," Annals of Operations Research, Springer, vol. 174(1), pages 169-183, February.
  3. Balaji Padmanabhan & Alexander Tuzhilin, 2003. "On the Use of Optimization for Data Mining: Theoretical Interactions and eCRM Opportunities," Management Science, INFORMS, vol. 49(10), pages 1327-1343, October.
  4. Orsenigo, Carlotta & Vercellis, Carlo, 2004. "Discrete support vector decision trees via tabu search," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 311-322, September.
  5. Wanpracha Art Chaovalitwongse, 2008. "Novel quadratic programming approach for time series clustering with biomedical application," Journal of Combinatorial Optimization, Springer, vol. 15(3), pages 225-241, April.
  6. P. S. Bradley & Usama M. Fayyad & O. L. Mangasarian, 1999. "Mathematical Programming for Data Mining: Formulations and Challenges," INFORMS Journal on Computing, INFORMS, vol. 11(3), pages 217-238, August.
  7. Heydari Majeed & Yousefli Amir, 2017. "A new optimization model for market basket analysis with allocation considerations: A genetic algorithm solution approach," Management & Marketing, Sciendo, vol. 12(1), pages 1-11, March.
  8. Lorenzo Gai & Federica Ielasi, 2014. "Operational drivers affecting credit risk of mutual guarantee institutions," Journal of Risk Finance, Emerald Group Publishing, vol. 15(3), pages 275-293, May.
  9. A. Astorino & A. Fuduli & M. Gaudioso, 2010. "DC models for spherical separation," Journal of Global Optimization, Springer, vol. 48(4), pages 657-669, December.
  10. B Baesens & C Mues & D Martens & J Vanthienen, 2009. "50 years of data mining and OR: upcoming trends and challenges," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 16-23, May.
  11. Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
  12. Zhengyu Ma & Hong Seo Ryoo, 2021. "Spherical Classification of Data, a New Rule-Based Learning Method," Journal of Classification, Springer;The Classification Society, vol. 38(1), pages 44-71, April.
  13. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
  14. R. Chandrasekaran & Young U. Ryu & Varghese S. Jacob & Sungchul Hong, 2005. "Isotonic Separation," INFORMS Journal on Computing, INFORMS, vol. 17(4), pages 462-474, November.
  15. J J Glen, 2005. "Mathematical programming models for piecewise-linear discriminant analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(3), pages 331-341, March.
  16. Olafsson, Sigurdur & Li, Xiaonan & Wu, Shuning, 2008. "Operations research and data mining," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1429-1448, June.
  17. A. Astorino & M. Gaudioso, 2002. "Polyhedral Separability Through Successive LP," Journal of Optimization Theory and Applications, Springer, vol. 112(2), pages 265-293, February.
  18. Emilio Carrizosa & Belen Martin-Barragan, 2011. "Maximizing upgrading and downgrading margins for ordinal regression," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 74(3), pages 381-407, December.
  19. Xeniya Vladimirovna Grigor’eva, 2016. "Approximate Functions in a Problem of Sets Separation," Journal of Optimization Theory and Applications, Springer, vol. 171(2), pages 550-572, November.
  20. Lean Yu & Zebin Yang & Ling Tang, 2016. "A novel multistage deep belief network based extreme learning machine ensemble learning paradigm for credit risk assessment," Flexible Services and Manufacturing Journal, Springer, vol. 28(4), pages 576-592, December.
  21. W. Nick Street, 2005. "Oblique Multicategory Decision Trees Using Nonlinear Programming," INFORMS Journal on Computing, INFORMS, vol. 17(1), pages 25-31, February.
  22. Lean Yu & Lihang Yu & Kaitao Yu, 2021. "A high-dimensionality-trait-driven learning paradigm for high dimensional credit classification," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-20, December.
  23. Pedro Duarte Silva, A., 2017. "Optimization approaches to Supervised Classification," European Journal of Operational Research, Elsevier, vol. 261(2), pages 772-788.
  24. J. J. Glen, 2004. "Dichotomous categorical variable formation in mathematical programming discriminant analysis models," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(4), pages 575-596, June.
  25. Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring," European Journal of Operational Research, Elsevier, vol. 195(3), pages 942-959, June.
  26. Lean Yu & Xinxie Li & Ling Tang & Zongyi Zhang & Gang Kou, 2015. "Social credit: a comprehensive literature review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-18, December.
  27. Guo, Yanhong & Zhou, Wenjun & Luo, Chunyu & Liu, Chuanren & Xiong, Hui, 2016. "Instance-based credit risk assessment for investment decisions in P2P lending," European Journal of Operational Research, Elsevier, vol. 249(2), pages 417-426.
  28. Emilio Carrizosa & Belen Martin-Barragan & Dolores Romero Morales, 2010. "Binarized Support Vector Machines," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 154-167, February.
  29. Meisel, Stephan & Mattfeld, Dirk, 2010. "Synergies of Operations Research and Data Mining," European Journal of Operational Research, Elsevier, vol. 206(1), pages 1-10, October.
  30. J. Paul Brooks, 2011. "Support Vector Machines with the Ramp Loss and the Hard Margin Loss," Operations Research, INFORMS, vol. 59(2), pages 467-479, April.
  31. Baldomero-Naranjo, Marta & Martínez-Merino, Luisa I. & Rodríguez-Chía, Antonio M., 2020. "Tightening big Ms in integer programming formulations for support vector machines with ramp loss," European Journal of Operational Research, Elsevier, vol. 286(1), pages 84-100.
  32. Stam, Antonie & Ungar, David R., 1995. "RAGNU: A microcomputer package for two-group mathematical programming-based nonparametric classification," European Journal of Operational Research, Elsevier, vol. 86(2), pages 374-388, October.
  33. Nieddu, Luciano & Patrizi, Giacomo, 2000. "Formal methods in pattern recognition: A review," European Journal of Operational Research, Elsevier, vol. 120(3), pages 459-495, February.
  34. Glen, J.J., 2006. "A comparison of standard and two-stage mathematical programming discriminant analysis methods," European Journal of Operational Research, Elsevier, vol. 171(2), pages 496-515, June.
  35. Xiao, Jin & Zhong, Yu & Jia, Yanlin & Wang, Yadong & Li, Ruoyi & Jiang, Xiaoyi & Wang, Shouyang, 2024. "A novel deep ensemble model for imbalanced credit scoring in internet finance," International Journal of Forecasting, Elsevier, vol. 40(1), pages 348-372.
  36. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, October.
  37. Brandner, Hubertus & Lessmann, Stefan & Voß, Stefan, 2013. "A memetic approach to construct transductive discrete support vector machines," European Journal of Operational Research, Elsevier, vol. 230(3), pages 581-595.
  38. Dimitris Bertsimas & Romy Shioda, 2007. "Classification and Regression via Integer Optimization," Operations Research, INFORMS, vol. 55(2), pages 252-271, April.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.