Normalized gaussian networks with mixed feature data

Authors:
Shu-Kay Ng;Geoffrey J. McLachlan
Affiliations:
Department of Mathematics, University of Queensland, Brisbane, QLD, Australia;Department of Mathematics, University of Queensland, Brisbane, QLD, Australia
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

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Abstract

With mixed feature data, problems are induced in modeling the gating network of normalized Gaussian (NG) networks as the assumption of multivariate Gaussian becomes invalid. In this paper, we propose an independence model to handle mixed feature data within the framework of NG networks. The method is illustrated using a real example of breast cancer data.