Information-based dichotomization: A method for multiclass Support Vector Machines

@article{Songsiri2008InformationbasedDA,
  title={Information-based dichotomization: A method for multiclass Support Vector Machines},
  author={Patoomsiri Songsiri and Boonserm Kijsirikul and Thimaporn Phetkaew},
  journal={2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)},
  year={2008},
  pages={3284-3291}
}
Approaches for solving a multiclass classification problem by support vector machines (SVMs) are typically to consider the problem as combination of two-class classification problems. Previous approaches have some limitations in classification accuracy and evaluation time. This paper proposes a novel method that employs information-based dichotomization for constructing a binary classification tree. Each node of the tree is a binary SVM with the minimum entropy. Our method can reduce the number… CONTINUE READING