Postprint version. Published in Advances in Data Analysis and Classification, Volume 1, Issue 1, March 1, 2007, pages 23-38.
The definitive version is available at https://doi.org/10.1007/s11634-006-0001-9.
In this paper, we discuss generalized mixture models and related semi-supervised learning methods, and show how they can be used to provide explicit methods for unknown class inference. After a brief description of standard mixture modeling and current model-based semi-supervised learning methods, we provide the generalization and discuss its computational implementation using three-stage expectation–maximization algorithm.
Statistics and Probability