Predicting conditional probability densities with the Gaussian mixture - RVFL network

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

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
• 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