370 search results - page 32 / 74 » Learning to rank from Bayesian decision inference |
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...
KDD
2007
ACM
14 years 8 months ago
2007
ACM
We present DL8, an exact algorithm for finding a decision tree that optimizes a ranking function under size, depth, accuracy and leaf constraints. Because the discovery of optimal...
KDD
2002
ACM
14 years 8 months ago
2002
ACM
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
UAI
2003
13 years 9 months ago
2003
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...