Classification of incomplete feature vectors by radial basis function networks

Article


Dybowski, Richard 1998. Classification of incomplete feature vectors by radial basis function networks. Pattern Recognition Letters. 19 (14), pp. 1257-1264.
AuthorsDybowski, Richard
Abstract

The paper describes the use of radial basis function neural networks with Gaussian basis functions to classify incomplete feature vectors. The method uses the fact that any marginal distribution of a Gaussian distribution can be determined from the mean vector and covariance matrix of the joint distribution.

KeywordsIncomplete Data; Gaussian mixture models; Radial basis functions; Imputation; EM algorithm; neural networks
JournalPattern Recognition Letters
Journal citation19 (14), pp. 1257-1264
ISSN0167-8655
Year1998
Accepted author manuscript
License
CC BY-ND
Web address (URL)http://dx.doi.org/10.1016/S0167-8655(98)00096-8
http://hdl.handle.net/10552/369
Publication dates
PrintJul 1998
Publication process dates
Deposited02 Nov 2009
Additional information

Citation:
Dybowski R. (1998) "Classification of incomplete feature vectors by radial basis function networks". Pattern Recognition Letters, 19 (14) 1257-1264.

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