Naslov
Likelihood based classification in Bayesian networks

Autori
Štajduhar, Ivan ; Bratko, Ivan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 25th IASTED International Multi-Conference: Artificial Intelligence and Applications / Devedžic, Vladan - Zürich : ACTA Press, 2007, 335-340

ISBN
978-0-88986-631-7

Skup
International Conference on Artificial Intelligence and Applications

Mjesto i datum
Innsbruck, Austrija, 12.02.2007. - 14.02.2007

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
machine learning; probabilistic networks; classification

Sažetak
Learning directed probabilistic networks from data and using them for classification purposes is a well known problem. Many learning algorithms have been shown to be successful for various kinds of learning scenarios. Basically they all generate a single network from data, which is then used for classification purposes and possible domain understanding. In this paper we propose a simple method for inferring a model consisting of several Bayesian networks, each one representing data of one class. The data is divided into class subsets and from each subset a separate Bayesian network is learnt. Classification is done using prior and posterior probability distribution information in all networks. We thoroughly tested the proposed method on synthetic data and several repository datasets and compared it to other machine learning methods, to prove its effectiveness. We argue that with smaller modifications, the method can be used for learning from censored survival domains.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA