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» Structure learning of Bayesian networks using constraints
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WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
15 years 5 months ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...
UAI
2007
15 years 1 months ago
"I Can Name that Bayesian Network in Two Matrixes!"
The traditional approach to building Bayesian networks is to build the graphical structure using a graphical editor and then add probabilities using a separate spreadsheet for eac...
Russell Almond
CE
2007
102views more  CE 2007»
14 years 11 months ago
Environmental design for a structured network learning society
Social interactions profoundly impact the learning processes of learners in traditional societies. The rapid rise of the Internet using population has been the establishment of nu...
Ben Chang, Nien-Heng Cheng, Yi-Chan Deng, Tak-Wai ...
VLDB
1998
ACM
147views Database» more  VLDB 1998»
15 years 4 months ago
Scalable Techniques for Mining Causal Structures
Mining for association rules in market basket data has proved a fruitful areaof research. Measures such as conditional probability (confidence) and correlation have been used to i...
Craig Silverstein, Sergey Brin, Rajeev Motwani, Je...
CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
15 years 5 months ago
Latent Structure Models for the Analysis of Gene Expression Data
Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
Dong Hua, Dechang Chen, Xiuzhen Cheng, Abdou Youss...