Abstract
Mixture Density Networks (MDNs) are a well-established method for modelling complex multi-valued functions where regression methods (such as MLPs) fail. In this paper we develop a Bayesian regularization method for MDNs by an extension of the evidence procedure. The method is tested on two data sets and compared with early stopping.
| Original language | English |
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| Title of host publication | IEE Conference Publication |
| Place of Publication | United Kingdom |
| Publisher | Institution of Engineering and Technology (IET) |
| Pages | 521-526 |
| Number of pages | 6 |
| Volume | 2 |
| Edition | 470 |
| ISBN (Print) | 0852967217 |
| Publication status | Published - 1999 |