Comparison of Hard and Probabilistic Evidence in Bayesian Model
| Autor: | Mahfoudhi Adel, Rebai Rim, Abid Mohamed, Maalej Mohamed Amin |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
business.industry Computer science Divergence-from-randomness model Probabilistic logic Bayesian network 02 engineering and technology Bayesian inference Machine learning computer.software_genre Bayesian statistics 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Bayesian programming Artificial intelligence Graphical model business Probabilistic relevance model computer |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783319534794 ISDA |
| DOI: | 10.1007/978-3-319-53480-0_61 |
| Popis: | Bayesian networks are powerful tools for probabilistic reasoning with uncertain evidences. Evidence originates from information based on the variables of observation. In this paper, we focus on two types of evidences: hard evidence and probabilistic evidence. We were interested in updating an evidence represented by a Bayesian model. This paper presents the application of probabilistic evidence in an adaptive user interface. Then, we compare the Bayesian model using probabilistic evidence with the Bayesian model using hard evidence. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|