Using Partially Labeled Data For Normal Mixture Identification With Application To Class Definition
- 24 August 2005
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 1603-1605
- https://doi.org/10.1109/igarss.1992.578645
Abstract
No abstract availableKeywords
This publication has 5 references indexed in Scilit:
- Asymptotic improvement of supervised learning by utilizing additional unlabeled samples: normal mixture density casePublished by SPIE-Intl Soc Optical Eng ,1992
- Goodness-of-Fit Statistics for Discrete Multivariate DataPublished by Springer Nature ,1988
- Mixture Densities, Maximum Likelihood and the EM AlgorithmSIAM Review, 1984
- Estimating the Dimension of a ModelThe Annals of Statistics, 1978
- Maximum Likelihood from Incomplete Data Via the EM AlgorithmJournal of the Royal Statistical Society Series B: Statistical Methodology, 1977