Results 281 to 290 of about 103,187 (313)

Evolutionary Bayesian Rose Trees

IEEE Transactions on Knowledge and Data Engineering, 2015
We present an evolutionary multi-branch tree clustering method to model hierarchical topics and their evolutionary patterns over time. The method builds evolutionary trees in a Bayesian online filtering framework. The tree construction is formulated as an online posterior estimation problem, which well balances both the fitness of the current tree and ...
Shixia Liu, Xiting Wang, Yangqiu Song, Baining Guo   +3 more
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A Bayesian guide to tree felling

Trends in Ecology & Evolution, 2000
To most evolutionary biologists, building phylogenetic trees is a bore. Comparative approaches to understanding patterns as diverse as the correlation of body size and brain size in primates, and the evolution of extended phenotypes in gallwasps, require a robust phylogeny on which to place changes in character state.
, Rokas, , McVean
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Tractable Bayesian social learning on trees

2012 IEEE International Symposium on Information Theory Proceedings, 2012
We study agents in a social network who learn by observing the actions of their neighbors. The agents iteratively estimate an unknown "state of the world" s from initial private signals, and the past actions of their neighbors in the social network. First, we consider a set of Bayesian agents, and investigate the computational problem the agents face ...
Yashodhan Kanoria, Omer Tamuz
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Bayesian Mapping of Lichens Growing on Trees

Biometrical Journal, 2001
Summary: Suitability of trees as hosts for epiphytic lichens are studied in a forest stand of size 25 ha. Suitability is measured as occupation probabilites which are modelled using hierarchical Bayesian approach. These probabilities are useful for an ecologist.
Riiali, Anne, Penttinen, Antti, Kuusinen, Mikko   +2 more
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Recursive Probability Trees for Bayesian Networks

2010
This paper proposes a new data structure for representing potentials. Recursive probability trees are a generalization of probability trees. Both structures are able to represent context-specific independencies, but the new one is also able to hold a potential in a factorized way.
Andrés Cano, Manuel Gómez-Olmedo, Serafín Moral, Cora B. Pérez-Ariza   +3 more
openaire   +1 more source

Online Learning with Bayesian Classification Trees

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Randomized classification trees are among the most popular machine learning tools and found successful applications in many areas. Although this classifier was originally designed as offline learning algorithm, there has been an increased interest in the last years to provide an online variant. In this paper, we propose an online learning algorithm for
Bulo, Samuel Rota, Kontschieder, Peter
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On Decision Trees for (1,2)-Bayesian Networks

Fundamenta Informaticae, 2002
Bayesian Networks (BN) are convenient tool for representation of probability distribution of variables. We study time complexity of decision trees which compute values of all observable variables from BN. We consider (1,2)-BN in which each node has at most 1 entering edge, and each variable has at most 2 values.
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Comparison of lazy Bayesian rule, and tree-augmented Bayesian learning

2002 IEEE International Conference on Data Mining, 2002. Proceedings., 2003
The naive Bayes classifier is widely used in interactive applications due to its computational efficiency, direct theoretical base, and competitive accuracy. However its attribute independence assumption can result in sub-optimal accuracy. A number of techniques have explored simple relaxations of the attribute independence assumption in order to ...
Zhihai Wang, Geoffrey I. Webb
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Building a bayesian factor tree from examples

2010 2nd International Workshop on Cognitive Information Processing, 2010
A criterion based on mutual information among variables is proposed for building a bayesian tree from a finite number of examples. The factor graph, in Forney-style form, can be used as an associative memory that performs probabilistic inference in data fusion applications. The procedure is explained with the aid of a fully-described example.
PALMIERI, Francesco, ROMANO, Gianmarco, SALVO ROSSI, Pierluigi, MATTERA D.   +3 more
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Use of fuzzy fault tree analysis and Bayesian network for occurrence likelihood estimation of navigational accidents in the Qinzhou Port

Ocean Engineering, 2022
Congcong Zhao, Tsz Leung Yip, Bing Wu
exaly