Neural networks for predicting Kaposi's sarcoma
| Autor: | J.R.W. Harris, Stephen J. Roberts, G.S. Patton, Dirk Husmeier, M.O. McClure |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Artificial neural network
business.industry Computer science Variable-order Markov model Posterior probability Monte Carlo method Markov process Markov chain Monte Carlo Machine learning computer.software_genre Markov model symbols.namesake symbols Artificial intelligence business Particle filter computer Gibbs sampling |
| Zdroj: | IJCNN |
| DOI: | 10.1109/ijcnn.1999.836274 |
| Popis: | This paper demonstrates a medical application of Bayesian neural networks, whose parameters and hyper-parameters are sampled from the posterior distribution by means of Monte Carlo Markov chain. The main objective is the determination of the relevance of various input variables. The paper focuses on typical difficulties one has to face when dealing with sparse data sets. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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