Bayes optimal kernel discriminant analysis

  title={Bayes optimal kernel discriminant analysis},
  author={Di You and Aleix M. Mart{\'i}nez},
  journal={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the originally nonlinearly separable data into a space of intrinsically much higher dimensionality where the data is linearly separable and can be readily classified with existing and efficient linear methods. For a given kernel function, the main challenge is to determine the parameters of the kernel which maps the original… CONTINUE READING