-
1
-
-
0002370418
-
A Tutorial on Learning with Bayexian Networks
-
M.I. Jordan, Editor, MIT Press. p
-
Heckerman, D., A Tutorial on Learning with Bayexian Networks, in Learning in Graphical Models, M.I. Jordan, Editor. 1998, MIT Press. p. 301-354.
-
(1998)
Learning in Graphical Models
, pp. 301-354
-
-
Heckerman, D.1
-
2
-
-
33845224362
-
Tutorial on MDL
-
P. Grunwald, I.J. Myung, and M.A. Pitt, Editors, The MIT Press
-
Grunwald, P., Tutorial on MDL, in Advances in Minimum Description Length: Theory and Applications, P. Grunwald, I.J. Myung, and M.A. Pitt, Editors. 2005, The MIT Press.
-
(2005)
Advances in Minimum Description Length: Theory and Applications
-
-
Grunwald, P.1
-
3
-
-
0031276011
-
Bayesian Network Classifiers
-
Friedman, N., D. Geiger, and M. Goldszmidt, Bayesian Network Classifiers. Machine Learning, 1997, 29: p. 131-163.
-
(1997)
Machine Learning
, vol.29
, pp. 131-163
-
-
Friedman, N.1
Geiger, D.2
Goldszmidt, M.3
-
4
-
-
0028482006
-
Learning Bayesian belief networks: An approach based on the MDL principle
-
Lam, W. and Bacchus, Learning Bayesian belief networks: An approach based on the MDL principle. Computational Intelligence, 1994. 10(4).
-
(1994)
Computational Intelligence
, vol.10
, Issue.4
-
-
Lam, W.1
Bacchus2
-
5
-
-
0345792473
-
Model Selection Based on Minimum Description Length
-
Grunwald, P., Model Selection Based on Minimum Description Length. Journal of Mathematical Psychology, 2000. 44: p. 133-152.
-
(2000)
Journal of Mathematical Psychology
, vol.44
, pp. 133-152
-
-
Grunwald, P.1
-
6
-
-
0008564212
-
Learning Bayesian Belief Networks based on the MDL principle: An efficient algorithm using the branch and bound technique
-
Bary, Italy
-
Suzuki, J. Learning Bayesian Belief Networks based on the MDL principle: An efficient algorithm using the branch and bound technique, in International Conference on Machine Learning. 1996. Bary, Italy.
-
(1996)
International Conference on Machine Learning
-
-
Suzuki, J.1
-
7
-
-
0008580731
-
Learning Bayesian Belief Networks based on the Minimum Description Length Principle: Basic Properties
-
Suzuki, J., Learning Bayesian Belief Networks based on the Minimum Description Length Principle: Basic Properties. IEICE Transactions on Fundamentals, 1999. E82-A(10): p. 2237-2245.
-
(1999)
IEICE Transactions on Fundamentals
, vol.E82-A
, Issue.10
, pp. 2237-2245
-
-
Suzuki, J.1
-
8
-
-
0011725472
-
An Overview of the Representation and Discovery of Causal Relationships using Bayesian Networks
-
C. Glymour and G.F. Cooper, Editors, AAAI Press, MIT Press, p
-
Cooper, G.F., An Overview of the Representation and Discovery of Causal Relationships using Bayesian Networks, in Computation, Causation & Discovery, C. Glymour and G.F. Cooper, Editors. 1999, AAAI Press / MIT Press, p. 3-62.
-
(1999)
Computation, Causation & Discovery
, pp. 3-62
-
-
Cooper, G.F.1
-
9
-
-
34249832377
-
A Bayesian Method for the Induction of Probabilistic Networks from Data
-
Cooper, G.F. and E. Herskovits, A Bayesian Method for the Induction of Probabilistic Networks from Data. Machine Learning, 1992. 9: p. 309-347.
-
(1992)
Machine Learning
, vol.9
, pp. 309-347
-
-
Cooper, G.F.1
Herskovits, E.2
-
10
-
-
0006178650
-
Learning Bayesian Networks from data: An information theory based approach
-
University of Ulster: Jordanstown, United Kingdom
-
Cheng, J., Learning Bayesian Networks from data: An information theory based approach, in Faculty of Informatics, University of Ulster, United Kingdom. 1998, University of Ulster: Jordanstown, United Kingdom.
-
(1998)
Faculty of Informatics, University of Ulster, United Kingdom
-
-
Cheng, J.1
-
12
-
-
0031345619
-
-
ACM
-
Cheng, J., Bell, D.A., Liu, W. Learning Belief Networks from Data: An Information Theory Based Approach, in Sixth ACM International Conference on Information and Knowledge Management. 1997: ACM.
-
(1997)
Learning Belief Networks from Data: An Information Theory Based Approach, in Sixth ACM International Conference on Information and Knowledge Management
-
-
Cheng, J.1
Bell, D.A.2
Liu, W.3
-
13
-
-
0003338515
-
Causation, Prediction and Search
-
First ed, ed. J. Berger, et al. Springer-Verlag
-
Spirtes, P., C. Glymour, and R. Scheines, Causation, Prediction and Search. First ed. Lecture Notes in Statistics, ed. J. Berger, et al. Vol. 81. 1993: Springer-Verlag. 526.
-
(1993)
Lecture Notes in Statistics
, vol.81
, pp. 526
-
-
Spirtes, P.1
Glymour, C.2
Scheines, R.3
-
14
-
-
0002996131
-
Akaike's Information Criterion and Recent Developments in Information Complexity
-
Bozdogan, H., Akaike's Information Criterion and Recent Developments in Information Complexity. Journal of Mathematical Psychology, 2000. 44: p. 62-91.
-
(2000)
Journal of Mathematical Psychology
, vol.44
, pp. 62-91
-
-
Bozdogan, H.1
-
15
-
-
34249761849
-
Learning Bayesian Networks: The combination of knowledge and statistical data
-
Heckerman, D., D. Geiger, and D.M. Chickering, Learning Bayesian Networks: The combination of knowledge and statistical data. Machine Learning, 1995.20: p. 197-243.
-
(1995)
Machine Learning
, vol.20
, pp. 197-243
-
-
Heckerman, D.1
Geiger, D.2
Chickering, D.M.3
-
16
-
-
33845188435
-
-
Cruz-Ramirez Nicandro, N.-F.L., Acosta-Mesa Hector Gabriel, Barrientos-Martinez Erandi, Rojas-Marcial Juan Efrain, A Parsimonious Constraint-based Algorithm to Induce Bayesian Network Structures from Data, in IEEE Proceedings of the Mexican International Conference on Computer Science ENC 2005, IEEE, Editor. 2005, IEEE: Puebla. p. 306-313.
-
Cruz-Ramirez Nicandro, N.-F.L., Acosta-Mesa Hector Gabriel, Barrientos-Martinez Erandi, Rojas-Marcial Juan Efrain, A Parsimonious Constraint-based Algorithm to Induce Bayesian Network Structures from Data, in IEEE Proceedings of the Mexican International Conference on Computer Science ENC 2005, IEEE, Editor. 2005, IEEE: Puebla. p. 306-313.
-
-
-
-
18
-
-
33845929195
-
-
Duda, R.O., Hart, Peter E., Stork, David G., Pattern Classification. 2001: John Wiley & Sons, INC.
-
Duda, R.O., Hart, Peter E., Stork, David G., Pattern Classification. 2001: John Wiley & Sons, INC.
-
-
-
-
19
-
-
0006999775
-
Learning Bayesian Networks from Data
-
University of California, Los Angeles: Los Angeles, California, p
-
Chickering, D.M., Learning Bayesian Networks from Data, in Computer Science, Cognitive Systems Laboratory. 1996, University of California, Los Angeles: Los Angeles, California, p. 172.
-
(1996)
Computer Science, Cognitive Systems Laboratory
, pp. 172
-
-
Chickering, D.M.1
-
20
-
-
84972488038
-
Bayesian Analysis in Expert Systems
-
Spiegelhalter, D.J., et al., Bayesian Analysis in Expert Systems. Statistical Science, 1993. 8(3): p. 219-247.
-
(1993)
Statistical Science
, vol.8
, Issue.3
, pp. 219-247
-
-
Spiegelhalter, D.J.1
-
21
-
-
33845945107
-
-
Norsys, www.norsys.com.
-
-
-
Norsys1
-
24
-
-
85164392958
-
A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
-
Montreal, Canada: Morgan Kaufmann
-
Kohavi, R. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection. in 14th International Joint Conference on Artificial Intelligence IJCAI'95. 1995a. Montreal, Canada: Morgan Kaufmann.
-
(1995)
14th International Joint Conference on Artificial Intelligence IJCAI'95
-
-
Kohavi, R.1
-
27
-
-
0042456371
-
An Algorithm for the Construction of Bayesian Network Structures from Data
-
Morgan Kaufmann
-
Singh, M., Valtorta, Marco. An Algorithm for the Construction of Bayesian Network Structures from Data, in 9th Conference on Uncertainty in Artificial Intelligence. 1993: Morgan Kaufmann.
-
(1993)
9th Conference on Uncertainty in Artificial Intelligence
-
-
Singh, M.1
-
28
-
-
0001173999
-
Construction of Bayesian Network Structures from Data: A Brief Survey and an Efficient Algorithm
-
Singh, M., Valtorta, Marco, Construction of Bayesian Network Structures from Data: a Brief Survey and an Efficient Algorithm. International Journal of Approximate Reasoning, 1995. 12: p. 111-131.
-
(1995)
International Journal of Approximate Reasoning
, vol.12
, pp. 111-131
-
-
Singh, M.1
|