Semi-Supervised Logistic Discrimination via Regularized Gaussian Basis Expansions

Shuichi Kawano, Sadanori Konishi
2011 Communications in Statistics - Theory and Methods  
The problem of constructing classification methods based on both classified and unclassified data sets is considered for analyzing data with complex structures. We introduce a semi-supervised logistic discriminant model with Gaussian basis expansions. Unknown parameters included in the logistic model are estimated by regularization method along with the technique of EM algorithm. For selection of adjusted parameters, we derive a model selection criterion from Bayesian viewpoints. Numerical
more » ... nts. Numerical studies are conducted to investigate the effectiveness of our proposed modeling procedures.
doi:10.1080/03610926.2010.481370 fatcat:4ruhbs5vs5a4nknppoxn7lyefy