Bayesian hierarchical kernel machines for nonlinear regression and classification
Sounak Chakraborty, Bani K. Mallick, Malay Ghosh · Oxford University Press eBooks · 2013
This chapter introduces Bayesian kernel based methods for regression and binary classification. The chapter is organized as follows. Section 4.2 describes the general regression and classification problem under the regularization framework and discusses a reproducing kernel Hilbert space (RKHS) and its related properties. Section 4.3 gives a detailed description of Bayesian kernel machine regression models and the associated prior justification. Section 4.4 discusses the Bayesian kernel machine model for binary classification problems. Finally, some concluding remarks and future possibilities are provided in Section 4.5.