-
1
-
-
4344710606
-
A new technique for combining multiple classifiers using the Dempster-Shafer theory of evidence
-
Al-Ani A., and Deriche M. A new technique for combining multiple classifiers using the Dempster-Shafer theory of evidence. J. Artif. Intell. Res. 17 (2002) 333-361
-
(2002)
J. Artif. Intell. Res.
, vol.17
, pp. 333-361
-
-
Al-Ani, A.1
Deriche, M.2
-
2
-
-
0019648059
-
-
J.A. Barnett, Computational methods for a mathematical theory of evidence, in: Proc. of 17th Joint Conference of Artificial Intelligence, 1981, pp. 868-875
-
J.A. Barnett, Computational methods for a mathematical theory of evidence, in: Proc. of 17th Joint Conference of Artificial Intelligence, 1981, pp. 868-875
-
-
-
-
3
-
-
50649097605
-
-
C.L. Blake, C.J.E. Keogh, UCI repository of machine learning databases, http://www.ics.uci.edu/mlearn/MLRepository.html
-
C.L. Blake, C.J.E. Keogh, UCI repository of machine learning databases, http://www.ics.uci.edu/mlearn/MLRepository.html
-
-
-
-
4
-
-
84975461176
-
-
Y. Bi, D. Bell, J.W. Guan, Combining evidence from classifiers in text categorization, in: Proc. of KES04, 2004, pp. 521-528
-
Y. Bi, D. Bell, J.W. Guan, Combining evidence from classifiers in text categorization, in: Proc. of KES04, 2004, pp. 521-528
-
-
-
-
5
-
-
50649102714
-
-
Y. Bi, Combining multiple classifiers for text categorization using the Dempster-Shafer theory of evidence, PhD thesis, University of Ulster, UK, 2004
-
Y. Bi, Combining multiple classifiers for text categorization using the Dempster-Shafer theory of evidence, PhD thesis, University of Ulster, UK, 2004
-
-
-
-
6
-
-
27644562157
-
On combining classifiers mass functions for text categorization
-
Bell D., Guan J.W., and Bi Y. On combining classifiers mass functions for text categorization. IEEE Trans. Knowledge Data Engrg. 17 10 (2005) 1307-1319
-
(2005)
IEEE Trans. Knowledge Data Engrg.
, vol.17
, Issue.10
, pp. 1307-1319
-
-
Bell, D.1
Guan, J.W.2
Bi, Y.3
-
7
-
-
42049089465
-
-
Y. Bi, J.W. Guan, An efficient triplet-based algorithm for evidential reasoning, in: Proc. of the 22nd Conference on Uncertainty in Artificial Intelligence, 2006, pp. 31-38
-
Y. Bi, J.W. Guan, An efficient triplet-based algorithm for evidential reasoning, in: Proc. of the 22nd Conference on Uncertainty in Artificial Intelligence, 2006, pp. 31-38
-
-
-
-
8
-
-
33750731980
-
-
Y. Bi, S.I. McClean, T. Anderson, On combining multiple classifiers using an evidential approach, in: Proc. of the Twenty-First National Conference on Artificial Intelligence (AAAI'06), 2006, pp. 324-329
-
Y. Bi, S.I. McClean, T. Anderson, On combining multiple classifiers using an evidential approach, in: Proc. of the Twenty-First National Conference on Artificial Intelligence (AAAI'06), 2006, pp. 324-329
-
-
-
-
9
-
-
0030211964
-
Bagging predictors
-
Breiman L. Bagging predictors. Machine Learning 24 2 (1996) 123-140
-
(1996)
Machine Learning
, vol.24
, Issue.2
, pp. 123-140
-
-
Breiman, L.1
-
10
-
-
0035478854
-
Random forests
-
Breiman L. Random forests. Machine Learning 45 1 (2001) 5-32
-
(2001)
Machine Learning
, vol.45
, Issue.1
, pp. 5-32
-
-
Breiman, L.1
-
11
-
-
0031361611
-
Machine learning research: Four current directions
-
Dietterich T. Machine learning research: Four current directions. AI Magazine 18 4 (1997) 97-136
-
(1997)
AI Magazine
, vol.18
, Issue.4
, pp. 97-136
-
-
Dietterich, T.1
-
12
-
-
0001823341
-
An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
-
Dietterich T. An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization. Machine Learning 1 22 (1998)
-
(1998)
Machine Learning
, vol.1
, Issue.22
-
-
Dietterich, T.1
-
13
-
-
80053403826
-
-
T. Dietterich, Ensemble methods in machine learning, in: Proc. 2nd Int. Workshop on Multiple Classifier Systems MCS2000, LNCS, vol. 1857, 2000, pp. 1-15
-
T. Dietterich, Ensemble methods in machine learning, in: Proc. 2nd Int. Workshop on Multiple Classifier Systems MCS2000, LNCS, vol. 1857, 2000, pp. 1-15
-
-
-
-
14
-
-
0000516376
-
Upper and lower probabilities induced by a multivalued mapping
-
Dempster A.P. Upper and lower probabilities induced by a multivalued mapping. Ann. Math. Stat. 38 (1967) 325-339
-
(1967)
Ann. Math. Stat.
, vol.38
, pp. 325-339
-
-
Dempster, A.P.1
-
15
-
-
37149055072
-
Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence
-
Denoeux T. Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence. Artif. Intell. 172 2-3 (2008) 234-264
-
(2008)
Artif. Intell.
, vol.172
, Issue.2-3
, pp. 234-264
-
-
Denoeux, T.1
-
16
-
-
0036786963
-
Approximating the combination of belief functions using the fast Moebius transform in a coarsened frame
-
Denoeux T., and Ben Yaghlane A. Approximating the combination of belief functions using the fast Moebius transform in a coarsened frame. Internat. J. Approx. Reason. 31 1-2 (2002) 77-101
-
(2002)
Internat. J. Approx. Reason.
, vol.31
, Issue.1-2
, pp. 77-101
-
-
Denoeux, T.1
Ben Yaghlane, A.2
-
17
-
-
0033902309
-
A neural network classifier based on Dempster-Shafer theory
-
Denoeux T. A neural network classifier based on Dempster-Shafer theory. IEEE Trans. Systems Man Cybernet. A 30 2 (2000) 131-150
-
(2000)
IEEE Trans. Systems Man Cybernet. A
, vol.30
, Issue.2
, pp. 131-150
-
-
Denoeux, T.1
-
18
-
-
0029307876
-
A k-nearest neighbor classification rule based on Dempster-Shafer theory
-
Denoeux T. A k-nearest neighbor classification rule based on Dempster-Shafer theory. IEEE Trans. Systems Man Cybern. 25 5 (1995) 804-813
-
(1995)
IEEE Trans. Systems Man Cybern.
, vol.25
, Issue.5
, pp. 804-813
-
-
Denoeux, T.1
-
19
-
-
84867038939
-
-
R.P.W. Duin, D.M.J. Tax, Experiments with classifier combining rules, in: J. Kittler, F. Roli (Eds.), Multiple Classifier Systems, 2000, pp. 16-29
-
R.P.W. Duin, D.M.J. Tax, Experiments with classifier combining rules, in: J. Kittler, F. Roli (Eds.), Multiple Classifier Systems, 2000, pp. 16-29
-
-
-
-
20
-
-
12144288329
-
Is combining classifiers with stacking better than selecting the best one?
-
Dzeroski S., and Zenko B. Is combining classifiers with stacking better than selecting the best one?. Machine Learning 54 3 (2004) 255-273
-
(2004)
Machine Learning
, vol.54
, Issue.3
, pp. 255-273
-
-
Dzeroski, S.1
Zenko, B.2
-
21
-
-
84970216868
-
The reliability of dichotomous judgments: unequal numbers of judgments per subject
-
Fleiss J.L., and Cuzick J. The reliability of dichotomous judgments: unequal numbers of judgments per subject. Appl. Psycholog. Meas. 3 (1979) 537-542
-
(1979)
Appl. Psycholog. Meas.
, vol.3
, pp. 537-542
-
-
Fleiss, J.L.1
Cuzick, J.2
-
22
-
-
50649123895
-
-
Y. Freund, R. Schapire, Experiments with a new boosting algorithm, in: Machine Learning: Proceedings of the Thirteenth International Conference, 1996, pp. 148-156
-
Y. Freund, R. Schapire, Experiments with a new boosting algorithm, in: Machine Learning: Proceedings of the Thirteenth International Conference, 1996, pp. 148-156
-
-
-
-
24
-
-
50649117980
-
-
J.W. Guan, D.A. Bell, Efficient algorithms for automated reasoning in expert systems, in: The 3rd IASTED International Conference on Robotics and Manufacturing, 1995, pp. 336-339
-
J.W. Guan, D.A. Bell, Efficient algorithms for automated reasoning in expert systems, in: The 3rd IASTED International Conference on Robotics and Manufacturing, 1995, pp. 336-339
-
-
-
-
25
-
-
0036719728
-
Are alternatives to Dempster's rule of combination real alternatives?: Comments on "about the belief function combination and the conflict management problem" Lefèvre et al.
-
Haenni R. Are alternatives to Dempster's rule of combination real alternatives?: Comments on "about the belief function combination and the conflict management problem" Lefèvre et al. Information Fusion 3 3 (2002) 237-239
-
(2002)
Information Fusion
, vol.3
, Issue.3
, pp. 237-239
-
-
Haenni, R.1
-
27
-
-
0032139235
-
The random subspace method for constructing decision forests
-
Ho T.K. The random subspace method for constructing decision forests. IEEE Trans. Pattern Anal. Machine Intell. 20 8 (1998) 832-844
-
(1998)
IEEE Trans. Pattern Anal. Machine Intell.
, vol.20
, Issue.8
, pp. 832-844
-
-
Ho, T.K.1
-
28
-
-
0032021555
-
On combining classifiers
-
Kittler J., Hatef M., Duin R.P.W., and Matas J. On combining classifiers. IEEE Trans. Pattern Anal. Machine Intell. 20 3 (1998) 226-239
-
(1998)
IEEE Trans. Pattern Anal. Machine Intell.
, vol.20
, Issue.3
, pp. 226-239
-
-
Kittler, J.1
Hatef, M.2
Duin, R.P.W.3
Matas, J.4
-
29
-
-
50649110176
-
-
L. Kuncheva, Combining classifiers: Soft computing solutions, in: S.K. Pal, A. Pal (Eds.), Pattern Recognition: From Classical to Modern Approaches, 2001, pp. 427-451
-
L. Kuncheva, Combining classifiers: Soft computing solutions, in: S.K. Pal, A. Pal (Eds.), Pattern Recognition: From Classical to Modern Approaches, 2001, pp. 427-451
-
-
-
-
30
-
-
0037403516
-
Measures of diversity in classifier ensembles
-
Kuncheva L., and Whitaker C.J. Measures of diversity in classifier ensembles. Machine Learning 51 (2003) 181-207
-
(2003)
Machine Learning
, vol.51
, pp. 181-207
-
-
Kuncheva, L.1
Whitaker, C.J.2
-
32
-
-
0031238275
-
Application of majority voting to pattern recognition: An analysis of its behavior and performance
-
Lam L., and Suen C.Y. Application of majority voting to pattern recognition: An analysis of its behavior and performance. IEEE Trans. Systems Man Cybernet. 27 5 (1997) 553-568
-
(1997)
IEEE Trans. Systems Man Cybernet.
, vol.27
, Issue.5
, pp. 553-568
-
-
Lam, L.1
Suen, C.Y.2
-
33
-
-
0030392357
-
-
L.S. Larkey, W.B. Croft, Combining classifiers in text categorization, in: Proceedings of SIGIR-96, 19th ACM International Conference on Research and Development in Information Retrieval, 1996, pp. 289-297
-
L.S. Larkey, W.B. Croft, Combining classifiers in text categorization, in: Proceedings of SIGIR-96, 19th ACM International Conference on Research and Development in Information Retrieval, 1996, pp. 289-297
-
-
-
-
34
-
-
1542455009
-
Reinvestigating Dempster's idea on evidence combination
-
Liu W., and Hong J. Reinvestigating Dempster's idea on evidence combination. Knowledge Inform. Syst. 2 2 (2000) 223-241
-
(2000)
Knowledge Inform. Syst.
, vol.2
, Issue.2
, pp. 223-241
-
-
Liu, W.1
Hong, J.2
-
35
-
-
33745854779
-
Analyzing the degree of conflict among belief functions
-
Liu W. Analyzing the degree of conflict among belief functions. Artif. Intell. 170 11 (2006) 909-924
-
(2006)
Artif. Intell.
, vol.170
, Issue.11
, pp. 909-924
-
-
Liu, W.1
-
36
-
-
85012722936
-
Combining the classification results of independent classifiers based on Dempster-Shafer theory of evidence
-
Mandler E.J., and Schurmann J. Combining the classification results of independent classifiers based on Dempster-Shafer theory of evidence. Pattern Recogn. Artif. Intell. X (1988) 381-393
-
(1988)
Pattern Recogn. Artif. Intell.
, vol.X
, pp. 381-393
-
-
Mandler, E.J.1
Schurmann, J.2
-
37
-
-
84880832861
-
-
P. Melville, R.J. Mooney, Constructing diverse classifier ensembles using artificial training examples, in: Proc. of IJCAI-03, 2003, pp. 505-510
-
P. Melville, R.J. Mooney, Constructing diverse classifier ensembles using artificial training examples, in: Proc. of IJCAI-03, 2003, pp. 505-510
-
-
-
-
39
-
-
0032596573
-
Feature selection for ensembles
-
AAAI Press
-
Opitz D. Feature selection for ensembles. Proc. of AAAI-99 (1999), AAAI Press 379-384
-
(1999)
Proc. of AAAI-99
, pp. 379-384
-
-
Opitz, D.1
-
40
-
-
33846058836
-
Pairwise classifier combination using belief functions
-
Quost B., Denoeux T., and Masson M.-H. Pairwise classifier combination using belief functions. Pattern Recogn. Lett. 28 5 (2007) 644-653
-
(2007)
Pattern Recogn. Lett.
, vol.28
, Issue.5
, pp. 644-653
-
-
Quost, B.1
Denoeux, T.2
Masson, M.-H.3
-
41
-
-
0002442796
-
Machine learning in automated text categorization
-
Sebastiani F. Machine learning in automated text categorization. ACM Comput. Surv. 34 1 (2002) 1-47
-
(2002)
ACM Comput. Surv.
, vol.34
, Issue.1
, pp. 1-47
-
-
Sebastiani, F.1
-
42
-
-
0027961797
-
Combining the results of several neural network classifiers
-
Rogova G. Combining the results of several neural network classifiers. Neural Networks 7 5 (1994) 777-781
-
(1994)
Neural Networks
, vol.7
, Issue.5
, pp. 777-781
-
-
Rogova, G.1
-
43
-
-
0023446625
-
Implementing Dempster's rule for hierarchical evidence
-
Shafer G., and Logan R. Implementing Dempster's rule for hierarchical evidence. Artif. Intell. 33 3 (1987) 271-298
-
(1987)
Artif. Intell.
, vol.33
, Issue.3
, pp. 271-298
-
-
Shafer, G.1
Logan, R.2
-
46
-
-
0025434991
-
-
Ph. Smets, The combination of evidence in the Transferable Belief Model, IEEE Trans. Pattern Anal. Machine Intell. 12 (5) 447-458
-
Ph. Smets, The combination of evidence in the Transferable Belief Model, IEEE Trans. Pattern Anal. Machine Intell. 12 (5) 447-458
-
-
-
-
48
-
-
0033713738
-
Combining multiple classifiers by averaging or by multiplying
-
Tax D.M.J., van Breukelen M., Duin R.P.W., and Kittler J. Combining multiple classifiers by averaging or by multiplying. Pattern Recognition 33 9 (2000) 1475-1485
-
(2000)
Pattern Recognition
, vol.33
, Issue.9
, pp. 1475-1485
-
-
Tax, D.M.J.1
van Breukelen, M.2
Duin, R.P.W.3
Kittler, J.4
-
49
-
-
33750696501
-
Combining of disparate classifiers through order statistics
-
Tumer K., and Robust G.J. Combining of disparate classifiers through order statistics. Pattern Anal. Appl. 6 1 (2002) 41-46
-
(2002)
Pattern Anal. Appl.
, vol.6
, Issue.1
, pp. 41-46
-
-
Tumer, K.1
Robust, G.J.2
-
50
-
-
0026860706
-
Several methods for combining multiple classifiers and their applications in handwritten character recognition
-
Xu L., Krzyzak A., and Suen C.Y. Several methods for combining multiple classifiers and their applications in handwritten character recognition. IEEE Trans. System Man Cybernet. 2 3 (1992) 418-435
-
(1992)
IEEE Trans. System Man Cybernet.
, vol.2
, Issue.3
, pp. 418-435
-
-
Xu, L.1
Krzyzak, A.2
Suen, C.Y.3
-
51
-
-
0032072012
-
An evidence-theoretic k-NN rule with parameter optimization
-
Zouhal L.M., and Denoeux T. An evidence-theoretic k-NN rule with parameter optimization. IEEE Trans. Systems Man Cybernet. C 28 2 (1998) 263-271
-
(1998)
IEEE Trans. Systems Man Cybernet. C
, vol.28
, Issue.2
, pp. 263-271
-
-
Zouhal, L.M.1
Denoeux, T.2
-
52
-
-
50649091490
-
-
Y. Yang, T. Ault, T. Pierce, Combining multiple learning strategies for effective cross validation, in: Proc. of ICML'00, 2000, pp. 1167-1182
-
Y. Yang, T. Ault, T. Pierce, Combining multiple learning strategies for effective cross validation, in: Proc. of ICML'00, 2000, pp. 1167-1182
-
-
-
-
53
-
-
0026122354
-
On the justification of Dempster's rule of combination
-
Voorbraak F. On the justification of Dempster's rule of combination. Artif. Intell. 48 2 (1991) 171-197
-
(1991)
Artif. Intell.
, vol.48
, Issue.2
, pp. 171-197
-
-
Voorbraak, F.1
-
54
-
-
0034247206
-
MultiBoosting: A technique for combining boosting and wagging
-
Webb G.I. MultiBoosting: A technique for combining boosting and wagging. Machine Learning 40 2 (2000) 159-196
-
(2000)
Machine Learning
, vol.40
, Issue.2
, pp. 159-196
-
-
Webb, G.I.1
-
55
-
-
0026692226
-
Stacked generalization
-
Wolpert D. Stacked generalization. Neural Networks 5 2 (1992) 241-259
-
(1992)
Neural Networks
, vol.5
, Issue.2
, pp. 241-259
-
-
Wolpert, D.1
|