-
1
-
-
0029484103
-
Survey and critique of techniques for extracting rules from trained artificial neural networks
-
Robert Andrews, Joachim Diederich, and Alan B. Tickle. Survey and critique of techniques for extracting rules from trained artificial neural networks. Knowledge-Based Systems, 8:373-389, 1995.
-
(1995)
Knowledge-Based Systems
, vol.8
, pp. 373-389
-
-
Andrews, R.1
Diederich, J.2
Tickle, A.B.3
-
5
-
-
55749090251
-
Polynomial calculation of the shapley value based on sampling
-
in print, doi: 10.1016/j.cor.2008.04.004
-
Javier Castro, Daniel Gómez, and Juan Tejada. Polynomial calculation of the shapley value based on sampling. Computers and Operations Research, 2008. (in print, doi: 10.1016/j.cor.2008.04.004).
-
(2008)
Computers and Operations Research
-
-
Castro, J.1
Gómez, D.2
Tejada, J.3
-
6
-
-
34447274515
-
Feature selection via coalitional game theory
-
Shay Cohen, Gideon Dror, and Eytan Ruppin. Feature selection via coalitional game theory. Neural Computation, 19(7):1939-1961, 2007.
-
(2007)
Neural Computation
, vol.19
, Issue.7
, pp. 1939-1961
-
-
Cohen, S.1
Dror, G.2
Ruppin, E.3
-
8
-
-
32344441116
-
Nomograms for visualizing support vector machines
-
New York, NY, USA. ACM. ISBN 1-59593-135-X
-
Aleks Jakulin, Martin Možina, Janez Demšar, Ivan Bratko, and Blaž Zupan. Nomograms for visualizing support vector machines. In KDD '05: Proceeding of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining, pages 108-117, New York, NY, USA, 2005. ACM. ISBN 1-59593-135-X.
-
(2005)
KDD ' 05: Proceeding of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining
, pp. 108-117
-
-
Jakulin, A.1
Možina, M.2
Demšar, J.3
Bratko, I.4
Zupan, B.5
-
9
-
-
3142713692
-
Fair attribution of functional contribution in artificial and biological networks
-
Alon Keinan, Ben Sandbank, Claus C. Hilgetag, IsaacMeilijson, and Eytan Ruppin. Fair attribution of functional contribution in artificial and biological networks. Neural Computation, 16(9):1887- 1915, 2004.
-
(2004)
Neural Computation
, vol.16
, Issue.9
, pp. 1887-1915
-
-
Keinan, A.1
Sandbank, B.2
Hilgetag, C.C.3
Meilijson, I.4
Ruppin, E.5
-
10
-
-
0031381525
-
Wrappers for feature subset selection
-
Ron Kohavi and George H. John. Wrappers for feature subset selection. Artificial Intelligence journal, 97(1-2):273-324, 1997.
-
(1997)
Artificial Intelligence Journal
, vol.97
, Issue.1-2
, pp. 273-324
-
-
Kohavi, R.1
John, G.H.2
-
11
-
-
0034922742
-
Machine learning for medical diagnosis: History, state of the art and perspective
-
Igor Kononenko. Machine learning for medical diagnosis: history, state of the art and perspective. Artificial Intelligence in Medicine, 23:89-109, 2001.
-
(2001)
Artificial Intelligence in Medicine
, vol.23
, pp. 89-109
-
-
Kononenko, I.1
-
14
-
-
34447292534
-
Comprehensible credit scoring models using rule extraction from support vector machines
-
DavidMartens, Bart Baesens, Tony Van Gestel, and Jan Vanthienen. Comprehensible credit scoring models using rule extraction from support vector machines. European Journal of Operational Research, 183(3):1466-1476, 2007.
-
(2007)
European Journal of Operational Research
, vol.183
, Issue.3
, pp. 1466-1476
-
-
Martens, D.1
Baesens, B.2
Van Gestel, T.3
Vanthienen, J.4
-
15
-
-
44649110114
-
Transversality of the shapley value
-
Stefano Moretti and Fioravante Patrone. Transversality of the shapley value. TOP, 16(1):1-41, 2008.
-
(2008)
TOP
, vol.16
, Issue.1
, pp. 1-41
-
-
Moretti, S.1
Patrone, F.2
-
16
-
-
33750710231
-
Nomograms for visualization of naive bayesian classifier
-
New York, NY, USA. Springer-Verlag New York, Inc. ISBN 3-540-23108-0
-
Martin Možina, Janez Demšar, Michael Kattan, and Blaž Zupan. Nomograms for visualization of naive bayesian classifier. In PKDD '04: Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, pages 337-348, New York, NY, USA, 2004. Springer-Verlag New York, Inc. ISBN 3-540-23108-0.
-
(2004)
PKDD ' 04: Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
, pp. 337-348
-
-
Možina, M.1
Demšar, J.2
Kattan, M.3
Zupan, B.4
-
17
-
-
67349104672
-
Generating rules with predicates, terms and variables from the pruned neural networks
-
Richi Nayak. Generating rules with predicates, terms and variables from the pruned neural networks. Neural Networks, 22(4):405-414, 2009.
-
(2009)
Neural Networks
, vol.22
, Issue.4
, pp. 405-414
-
-
Nayak, R.1
-
21
-
-
33750708213
-
Visual explanation of evidence in additive classifiers
-
Duane Szafron, Brett Poulin, Roman Eisner, Paul Lu, Russ Greiner, David Wishart, Alona Fyshe, Brandon Pearcy, Cam Macdonell, and John Anvik. Visual explanation of evidence in additive classifiers. In Proceedings of Innovative Applications of Artificial Intelligence, 2006.
-
(2006)
Proceedings of Innovative Applications of Artificial Intelligence
-
-
Szafron, D.1
Poulin, B.2
Eisner, R.3
Lu, P.4
Greiner, R.5
Wishart, D.6
Fyshe, A.7
Pearcy, B.8
MacDonell, C.9
Anvik, J.10
-
22
-
-
0027678679
-
Extracting refined rules from knowledge-based neural networks, machine learning
-
Geoffrey Towell and Jude W. Shavlik. Extracting refined rules from knowledge-based neural networks, machine learning. Machine Learning, 13:71-101, 1993.
-
(1993)
Machine Learning
, vol.13
, pp. 71-101
-
-
Towell, G.1
Shavlik, J.W.2
-
23
-
-
69249209926
-
Explaining instance classifications with interactions of subsets of feature values
-
Erik Štrumbelj, Igor Kononenko, and Marko Robnik Šikonja. Explaining instance classifications with interactions of subsets of feature values. Data & Knowledge Engineering, 68(10):886-904, 2009.
-
(2009)
Data & Knowledge Engineering
, vol.68
, Issue.10
, pp. 886-904
-
-
Štrumbelj, E.1
Kononenko, I.2
Šikonja, M.R.3
|