Selection of Import Vectors via Binary Particle Swarm Optimization and Cross-Validation for Kernel Logistic Regression

@article{Tanaka2007SelectionOI,
  title={Selection of Import Vectors via Binary Particle Swarm Optimization and Cross-Validation for Kernel Logistic Regression},
  author={Kenji Tanaka and Takio Kurita and Tohru Kawabe},
  journal={2007 International Joint Conference on Neural Networks},
  year={2007},
  pages={1037-1042}
}
Kernel logistic regression (KLR) is a powerful discriminative algorithm. It has similar loss function and algorithmic structure to the kernel support vector machine (SVM). Recently, Zhu and Hastie proposed the import vector machine (IVM) in which a subset of the input vectors of KLR are selected by minimizing the regularized negative log-likelihood to… CONTINUE READING