-
8
-
-
34249832377
-
Bayesian method for the induction of probabilistic networks from data
-
G. Cooper and E. Herskovits. Bayesian method for the induction of probabilistic networks from data. Machine Learning, 9(4):309-347, 1992.
-
(1992)
Machine Learning
, vol.9
, Issue.4
, pp. 309-347
-
-
Cooper, G.1
Herskovits, E.2
-
11
-
-
24644467293
-
Locally weighted naive bayes
-
Acapulco, Mexico
-
E. Frank, M. Hall, and B. Pfahringer. Locally weighted naive bayes. In Proceedings of the 19th Conference on Uncertainty in Artificial Intelligence, pages 249-256, Acapulco, Mexico, 2003.
-
(2003)
Proceedings of the 19th Conference on Uncertainty in Artificial Intelligence
, pp. 249-256
-
-
Frank, E.1
Hall, M.2
Pfahringer, B.3
-
12
-
-
0031276011
-
Bayesian network classifiers
-
N. Friedman, D. Geiger, and M. Goldszmidt. Bayesian network classifiers. Machine Learning, 29(2-3):131-163, 1997.
-
(1997)
Machine Learning
, vol.29
, Issue.2-3
, pp. 131-163
-
-
Friedman, N.1
Geiger, D.2
Goldszmidt, M.3
-
13
-
-
0001942829
-
Neural networks and the bias/variance dilemma
-
S. German, E. Bienenstock, and R. Doursat. Neural networks and the bias/variance dilemma. Neural Computation, 4(1):1-58, 1992.
-
(1992)
Neural Computation
, vol.4
, Issue.1
, pp. 1-58
-
-
German, S.1
Bienenstock, E.2
Doursat, R.3
-
17
-
-
31844453166
-
Efficient discriminative learning of bayesian network classifier via boosted augmented naive bayes
-
Bonn, Germany
-
Y. Jing, V. Pavlovíc, and J. M. Rehg. Efficient discriminative learning of bayesian network classifier via boosted augmented naive bayes. In Proceedings of the 22nd International Conference on Machine learning, pages 369-376, Bonn, Germany, 2005.
-
(2005)
Proceedings of the 22nd International Conference on Machine Learning
, pp. 369-376
-
-
Jing, Y.1
Pavlovíc, V.2
Rehg, J.M.3
-
20
-
-
0026992322
-
An analysis of Bayesian classifiers
-
San Jose, CA
-
P. Langley, W. Iba, and K. Thompson. An analysis of Bayesian classifiers. In Proceedings of the 10th National Conference on Artificial Intelligence, pages 223-228, San Jose, CA, 1992.
-
(1992)
Proceedings of the 10th National Conference on Artificial Intelligence
, pp. 223-228
-
-
Langley, P.1
Iba, W.2
Thompson, K.3
-
21
-
-
0141607834
-
The representational power of discrete Bayesian networks
-
C. X. Ling and H. Zhang. The representational power of discrete Bayesian networks. Journal of Machine Learning Research, 3:709-721, 2003.
-
(2003)
Journal of Machine Learning Research
, vol.3
, pp. 709-721
-
-
Ling, C.X.1
Zhang, H.2
-
22
-
-
0032328510
-
On the complexity of a practical interior-point method
-
S. G. Nash and A. Sofer. On the complexity of a practical interior-point method. SIAM Journal on Optimization, 8(3):833-849, 1998.
-
(1998)
SIAM Journal on Optimization
, vol.8
, Issue.3
, pp. 833-849
-
-
Nash, S.G.1
Sofer, A.2
-
24
-
-
21244467519
-
On discriminative bayesian network classifiers and logistic regression
-
T. Roos, H. Wettig, P. Grünwald, P. Myllymäki, and H. Tirri. On discriminative bayesian network classifiers and logistic regression. Machine Learning, 59(3):267-296, 2005.
-
(2005)
Machine Learning
, vol.59
, Issue.3
, pp. 267-296
-
-
Roos, T.1
Wettig, H.2
Grünwald, P.3
Myllymäki, P.4
Tirri, H.5
-
28
-
-
0034247206
-
Multiboosting: A technique for combining Boosting and Wagging
-
G. I. Webb. Multiboosting: A technique for combining Boosting and Wagging. Machine Learning, 40(2):159-196, 2000.
-
(2000)
Machine Learning
, vol.40
, Issue.2
, pp. 159-196
-
-
Webb, G.I.1
-
29
-
-
14844351034
-
Not so naive Bayes: Aggregating one-dependence estimators
-
G. I. Webb, J. Boughton, and Z. Wang. Not so naive Bayes: Aggregating one-dependence estimators. Machine Learning, 58(1):5-24, 2005.
-
(2005)
Machine Learning
, vol.58
, Issue.1
, pp. 5-24
-
-
Webb, G.I.1
Boughton, J.2
Wang, Z.3
-
31
-
-
35648962940
-
To select or to weigh: A comparative study of linear combination schemes for superparent-one-dependence estimators
-
Y. Yang, G. I. Webb, J. Cerquidesz, K. Korb, J. Boughton, and K-M. Ting. To select or to weigh: A comparative study of linear combination schemes for superparent-one-dependence estimators. IEEE Transactions on Knowledge and Data Engineering, 9(12):1652-1665, 2007.
-
(2007)
IEEE Transactions on Knowledge and Data Engineering
, vol.9
, Issue.12
, pp. 1652-1665
-
-
Yang, Y.1
Webb, G.I.2
Cerquidesz, J.3
Korb, K.4
Boughton, J.5
Ting, K.-M.6
-
32
-
-
29344462495
-
Hidden naive Bayes
-
Pittsburgh, PA
-
H. Zhang, L. Jiang, and J. Su. Hidden naive Bayes. In Proceedings of the 20th National Conference on Artificial Intelligence, pages 919-924, Pittsburgh, PA, 2005.
-
(2005)
Proceedings of the 20th National Conference on Artificial Intelligence
, pp. 919-924
-
-
Zhang, H.1
Jiang, L.2
Su, J.3
-
33
-
-
84884333463
-
A comparative study of semi-naive Bayes methods in classification learning
-
Sydney, Australia
-
F. Zheng and G. I. Webb. A comparative study of semi-naive Bayes methods in classification learning. In Proceedings of the 4th Australasian Data Mining Conference, pages 141- 156, Sydney, Australia, 2005.
-
(2005)
Proceedings of the 4th Australasian Data Mining Conference
, pp. 141-156
-
-
Zheng, F.1
Webb, G.I.2
-
35
-
-
38049141398
-
Finding the right family: Parent and child selection for averaged one-dependence estimators
-
Warsaw, Poland
-
F. Zheng and G. I. Webb. Finding the right family: Parent and child selection for averaged one-dependence estimators. In Proceedings of the 18th European Conference on Machine Learning, pages 490-501, Warsaw, Poland, 2007.
-
(2007)
Proceedings of the 18th European Conference on Machine Learning
, pp. 490-501
-
-
Zheng, F.1
Webb, G.I.2
-
36
-
-
0034301677
-
Lazy learning of Bayesian rules
-
Z. Zheng and G. I. Webb. Lazy learning of Bayesian rules. Machine Learning, 41(1):53-84, 2000.
-
(2000)
Machine Learning
, vol.41
, Issue.1
, pp. 53-84
-
-
Zheng, Z.1
Webb, G.I.2
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