Husmeier, D. and Taylor, J.G. (1997) Predicting conditional probability densities with the Gaussian mixture - RVFL network. In: Smith, G.D., Steele, N.C. and Albrecht, R.F. (eds.) Artificial Neural Networks and Genetic Algorithms. Series: Springer computer science. Springer: Wien, Germany, pp. 477-481. ISBN 9783211830871
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Abstract
The incorporation of the Random Vector Functional Link (RVFL) concept into mixture models for predicting conditional probability densities achieves a considerable speed-up of the training process. This al lows the creation of a large ensemble of predictors, which results in an improvement in the generalization performance.
Item Type: | Book Sections |
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Status: | Published |
Glasgow Author(s) Enlighten ID: | Husmeier, Professor Dirk |
Authors: | Husmeier, D., and Taylor, J.G. |
College/School: | College of Science and Engineering > School of Mathematics and Statistics > Statistics |
Publisher: | Springer |
ISBN: | 9783211830871 |
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