31 search results - page 3 / 7 » Learning Markov Network Structure using Few Independence Tes... |
UAI
2001
13 years 6 months ago
2001
In this paper we present a method of computing the posterior probability of conditional independence of two or more continuous variables from data, examined at several resolutions...
ADMA
2006
Springer
13 years 11 months ago
2006
Springer
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
KDD
2003
ACM
14 years 5 months ago
2003
ACM
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
NIPS
2003
13 years 6 months ago
2003
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
AI
2002
Springer
13 years 5 months ago
2002
Springer
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...