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» Lazy Learning of Bayesian Rules
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ICML
2006
IEEE
14 years 7 months ago
Efficient lazy elimination for averaged one-dependence estimators
Semi-naive Bayesian classifiers seek to retain the numerous strengths of naive Bayes while reducing error by weakening the attribute independence assumption. Backwards Sequential ...
Fei Zheng, Geoffrey I. Webb
EMNLP
2009
13 years 4 months ago
Bayesian Learning of Phrasal Tree-to-String Templates
We examine the problem of overcoming noisy word-level alignments when learning tree-to-string translation rules. Our approach introduces new rules, and reestimates rule probabilit...
Ding Liu, Daniel Gildea
ECAI
2004
Springer
13 years 11 months ago
Exploiting Association and Correlation Rules - Parameters for Improving the K2 Algorithm
A Bayesian network is an appropriate tool to deal with the uncertainty that is typical of real-life applications. Bayesian network arcs represent statistical dependence between dif...
Evelina Lamma, Fabrizio Riguzzi, Sergio Storari
DSS
2007
127views more  DSS 2007»
13 years 6 months ago
Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
AGI
2011
12 years 10 months ago
Reinforcement Learning and the Bayesian Control Rule
We present an actor-critic scheme for reinforcement learning in complex domains. The main contribution is to show that planning and I/O dynamics can be separated such that an intra...
Pedro Alejandro Ortega, Daniel Alexander Braun, Si...