Max Margin Polyhedral Conic Function Classifier

Orturk G., CEYLAN G.

International Conference on Computational Science and Computational Intelligence (CSIC), Nevada, United States Of America, 15 - 17 December 2016, pp.1395-1396 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/csci.2016.265
  • City: Nevada
  • Country: United States Of America
  • Page Numbers: pp.1395-1396
  • Keywords: Classification, SVM, GEPSVM, PCF
  • Anadolu University Affiliated: Yes


In classification problems, generalization ability has a key role for successful prediction. Well known Support Vector Machine classifier, tries to increase generalization ability via maximizing the margin, which is the distance between two parallel hyperplanes on the closest points. In this work we investigate maximizing the margin on non-parallel multi surfaces, by adapting GEPSVM* to Polyhedral Conic Function Classifiers.