253 search results - page 17 / 51 » Learning Bayesian Networks by Evolution for Classifier Combi... |
AUSAI
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
IDEAL
2004
Springer
14 years 1 months ago
2004
Springer
Abstract. Multiple classifier systems based on neural networks can give improved generalisation performance as compared with single classifier systems. We examine collaboration in ...
GECCO
2009
Springer
13 years 11 months ago
2009
Springer
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
JMLR
2012
11 years 10 months ago
2012
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
TIP
2008
13 years 7 months ago
2008
In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...